Jekyll2023-02-28T13:39:50+00:00https://jon.glass/feed.xmlHalf Full of SecuritySharpening the ACKs since 2013ChatGPT wrote this blog post2023-02-27T17:33:28+00:002023-02-27T17:33:28+00:00https://jon.glass/blog/chatgpt-writes-the-blog<p>This is what I got from ChatGPT when I provided the following prompt:</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>Write a 500 word technical blog post about the Microsoft Defender for Endpoint API to perform Incident Response with Python examples
</code></pre></div></div>
<p>Microsoft Defender for Endpoint is a comprehensive, cloud-based endpoint security solution that provides real-time protection against a wide range of cyber threats. It offers an API that allows security teams to integrate the platform with their existing security tools and workflows. In this blog post, we will explore how to use the Microsoft Defender for Endpoint API to perform incident response with Python examples.</p>
<p>Before we dive into the technical details, it’s important to note that using the Microsoft Defender for Endpoint API requires a valid subscription to the service. If you do not have access to the platform, you can sign up for a free trial to test the API.</p>
<p>The Microsoft Defender for Endpoint API provides a rich set of features for incident response. These include:</p>
<ul>
<li>Retrieving alerts and incidents</li>
<li>Getting details about devices and endpoints</li>
<li>Querying security events and alerts</li>
<li>Retrieving and analyzing files</li>
<li>Managing remediation actions
To use the API, you will need to authenticate with Azure Active Directory (AAD) and obtain an access token. This token will be used to make requests to the API endpoints. Here is an example of how to obtain an access token using the AAD Authentication Library (ADAL) in Python:</li>
</ul>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">tenant_id</span> <span class="o">=</span> <span class="s">'your_tenant_id'</span>
<span class="n">client_id</span> <span class="o">=</span> <span class="s">'your_client_id'</span>
<span class="n">client_secret</span> <span class="o">=</span> <span class="s">'your_client_secret'</span>
<span class="n">context</span> <span class="o">=</span> <span class="n">adal</span><span class="p">.</span><span class="n">AuthenticationContext</span><span class="p">(</span><span class="sa">f</span><span class="s">'https://login.microsoftonline.com/</span><span class="si">{</span><span class="n">tenant_id</span><span class="si">}</span><span class="s">'</span><span class="p">)</span>
<span class="n">token</span> <span class="o">=</span> <span class="n">context</span><span class="p">.</span><span class="n">acquire_token_with_client_credentials</span><span class="p">(</span><span class="s">'https://api.securitycenter.microsoft.com'</span><span class="p">,</span> <span class="n">client_id</span><span class="p">,</span> <span class="n">client_secret</span><span class="p">)</span>
<span class="n">access_token</span> <span class="o">=</span> <span class="n">token</span><span class="p">.</span><span class="n">get</span><span class="p">(</span><span class="s">'accessToken'</span><span class="p">)</span>
</code></pre></div></div>
<p>Once you have obtained an access token, you can use it to authenticate your requests to the API endpoints. Here is an example of how to retrieve a list of all alerts:</p>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="kn">import</span> <span class="nn">requests</span>
<span class="n">url</span> <span class="o">=</span> <span class="s">'https://api.securitycenter.microsoft.com/api/alerts'</span>
<span class="n">headers</span> <span class="o">=</span> <span class="p">{</span><span class="s">'Authorization'</span><span class="p">:</span> <span class="sa">f</span><span class="s">'Bearer </span><span class="si">{</span><span class="n">access_token</span><span class="si">}</span><span class="s">'</span><span class="p">}</span>
<span class="n">response</span> <span class="o">=</span> <span class="n">requests</span><span class="p">.</span><span class="n">get</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">headers</span><span class="o">=</span><span class="n">headers</span><span class="p">)</span>
<span class="n">alerts</span> <span class="o">=</span> <span class="n">response</span><span class="p">.</span><span class="n">json</span><span class="p">()</span>
</code></pre></div></div>
<p>This will retrieve a JSON object containing information about all alerts in the Microsoft Defender for Endpoint platform.</p>
<p>To retrieve information about a specific alert, you can use the alert ID to make a request to the API. Here is an example:</p>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">alert_id</span> <span class="o">=</span> <span class="s">'your_alert_id'</span>
<span class="n">url</span> <span class="o">=</span> <span class="sa">f</span><span class="s">'https://api.securitycenter.microsoft.com/api/alerts/</span><span class="si">{</span><span class="n">alert_id</span><span class="si">}</span><span class="s">'</span>
<span class="n">response</span> <span class="o">=</span> <span class="n">requests</span><span class="p">.</span><span class="n">get</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">headers</span><span class="o">=</span><span class="n">headers</span><span class="p">)</span>
<span class="n">alert</span> <span class="o">=</span> <span class="n">response</span><span class="p">.</span><span class="n">json</span><span class="p">()</span>
</code></pre></div></div>
<p>This will retrieve a JSON object containing detailed information about the specified alert.</p>
<p>You can also use the API to retrieve information about a specific device or endpoint. Here is an example:</p>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">device_id</span> <span class="o">=</span> <span class="s">'your_device_id'</span>
<span class="n">url</span> <span class="o">=</span> <span class="sa">f</span><span class="s">'https://api.securitycenter.microsoft.com/api/machines/</span><span class="si">{</span><span class="n">device_id</span><span class="si">}</span><span class="s">'</span>
<span class="n">response</span> <span class="o">=</span> <span class="n">requests</span><span class="p">.</span><span class="n">get</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">headers</span><span class="o">=</span><span class="n">headers</span><span class="p">)</span>
<span class="n">device</span> <span class="o">=</span> <span class="n">response</span><span class="p">.</span><span class="n">json</span><span class="p">()</span>
</code></pre></div></div>
<p>This will retrieve a JSON object containing information about the specified device or endpoint.</p>
<p>Another useful feature of the Microsoft Defender for Endpoint API is the ability to retrieve and analyze files. Here is an example of how to retrieve a file and analyze it using the API:</p>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">file_id</span> <span class="o">=</span> <span class="s">'your_file_id'</span>
<span class="n">url</span> <span class="o">=</span> <span class="sa">f</span><span class="s">'https://api.securitycenter.microsoft.com/api/files/</span><span class="si">{</span><span class="n">file_id</span><span class="si">}</span><span class="s">'</span>
<span class="n">response</span> <span class="o">=</span> <span class="n">requests</span><span class="p">.</span><span class="n">get</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">headers</span><span class="o">=</span><span class="n">headers</span><span class="p">)</span>
<span class="n">file_content</span> <span class="o">=</span> <span class="n">response</span><span class="p">.</span><span class="n">content</span>
<span class="n">analysis_url</span> <span class="o">=</span> <span class="s">'https://api.securitycenter.microsoft.com/api/analysis'</span>
<span class="n">data</span> <span class="o">=</span> <span class="p">{</span><span class="s">'content'</span><span class="p">:</span> <span class="n">file_content</span><span class="p">}</span>
<span class="n">response</span> <span class="o">=</span> <span class="n">requests</span><span class="p">.</span><span class="n">post</span><span class="p">(</span><span class="n">analysis_url</span><span class="p">,</span> <span class="n">headers</span><span class="o">=</span><span class="n">headers</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">)</span>
<span class="n">analysis_result</span> <span class="o">=</span> <span class="n">response</span><span class="p">.</span><span class="n">json</span><span class="p">()</span>
</code></pre></div></div>
<p>This will retrieve the contents of the specified file and submit it to the Microsoft Defender for Endpoint cloud for analysis. The API will return a JSON object containing the analysis result.</p>
<p>Finally, you can use the Microsoft Defender for Endpoint API to manage remediation actions.</p>Microsoft 365 Security: Running Arbitrary Commands via the API2022-03-13T17:33:28+00:002022-03-13T17:33:28+00:00https://jon.glass/blog/Running-Arbitrary-Commands<h2 id="running-arbitrary-commands-on-an-endpoint-via-the-api">Running Arbitrary Commands on an Endpoint via the API</h2>
<p>Microsoft Defender’s Live Response is a delightful addition to your Incident Response toolbelt, but it does have a particularly irksome deficiency. As of publication, it does not allow execution of arbitrary commands. I know. Ridiculous right? Well there is an simple fix for this…</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>C:\windows\system32\cmd.exe /c $args
</code></pre></div></div>
<p>yeah…that simple.
<img 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" alt="cmd.ps1" /></p>
<p>All we need to do now is upload it to our Live Response Library like we did in my previous post…</p>
<h2 id="uploading-cmdps1-to-the-live-response-library">Uploading cmd.ps1 to the Live Response Library</h2>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">script</span> <span class="o">=</span> <span class="s">"""
C:\windows\system32\cmd.exe /c $args
"""</span>
<span class="n">fileobj</span> <span class="o">=</span> <span class="n">StringIO</span><span class="p">(</span><span class="n">script</span><span class="p">)</span>
<span class="n">fileobj</span><span class="p">.</span><span class="n">filename</span> <span class="o">=</span> <span class="s">"cmd.ps1"</span>
<span class="n">postFileToLiveResponseLibrary</span><span class="p">(</span>
<span class="n">fileObjToUpload</span> <span class="o">=</span> <span class="n">fileobj</span><span class="p">,</span>
<span class="n">description</span> <span class="o">=</span> <span class="s">"Allows you to run arbitrary commands. Simply put the commands into the script parameters."</span><span class="p">,</span>
<span class="n">parameters</span> <span class="o">=</span> <span class="s">"Command you want to Run. Example: dir /s /b c:\ > cdrive.txt"</span><span class="p">,</span>
<span class="n">override</span> <span class="o">=</span> <span class="bp">True</span>
<span class="p">)</span>
</code></pre></div></div>
<p>Output:</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>{'@odata.context': 'https://api.securitycenter.windows.com/api/$metadata#LibraryFiles/$entity',
'fileName': 'cmd.ps1',
'sha256': '8e1bc75666cede5d95cf422e413bf5ebd691a4cb0fbf768e5ed398c1624cb4eb',
'description': 'Allows you to run arbitrary commands. Simply put the commands into the script parameters.',
'creationTime': '2022-03-12T17:25:28.743863Z',
'lastUpdatedTime': '2022-03-12T17:25:28.743863Z',
'createdBy': 'Jonathan Glass',
'hasParameters': False,
'parametersDescription': 'Command you want to Run. Example: dir /s /b c:\\ > cdrive.txt'}
</code></pre></div></div>
<h2 id="executing-arbitrary-commands-using-cmdps1-via-the-api">Executing Arbitrary Commands using cmd.ps1 via the API</h2>
<h3 id="building-the-command-sequence">Building the command sequence</h3>
<p>This is a quick a method of compiling the json needed. Might not be perfect..</p>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code>
<span class="k">def</span> <span class="nf">addFileFromLibrary</span><span class="p">(</span><span class="n">FileName</span><span class="p">):</span>
<span class="n">command</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">command</span><span class="p">[</span><span class="s">'type'</span><span class="p">]</span> <span class="o">=</span> <span class="s">"PutFile"</span>
<span class="n">command</span><span class="p">[</span><span class="s">"params"</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">command</span><span class="p">[</span><span class="s">"params"</span><span class="p">].</span><span class="n">append</span><span class="p">({</span><span class="s">"key"</span><span class="p">:</span><span class="s">"FileName"</span><span class="p">,</span><span class="s">"value"</span><span class="p">:</span><span class="n">FileName</span><span class="p">})</span>
<span class="k">return</span> <span class="n">command</span>
<span class="k">def</span> <span class="nf">addCmdToCommandList</span><span class="p">(</span><span class="n">cmdline</span><span class="p">):</span>
<span class="n">command</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">command</span><span class="p">[</span><span class="s">'type'</span><span class="p">]</span> <span class="o">=</span> <span class="s">"RunScript"</span>
<span class="n">command</span><span class="p">[</span><span class="s">"params"</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">command</span><span class="p">[</span><span class="s">"params"</span><span class="p">].</span><span class="n">append</span><span class="p">({</span><span class="s">"key"</span><span class="p">:</span><span class="s">"ScriptName"</span><span class="p">,</span><span class="s">"value"</span><span class="p">:</span><span class="s">"cmd.ps1"</span><span class="p">})</span>
<span class="n">command</span><span class="p">[</span><span class="s">"params"</span><span class="p">].</span><span class="n">append</span><span class="p">({</span><span class="s">"key"</span><span class="p">:</span><span class="s">"Args"</span><span class="p">,</span><span class="s">"value"</span><span class="p">:</span><span class="nb">str</span><span class="p">(</span><span class="n">cmdline</span><span class="p">)})</span>
<span class="k">return</span> <span class="n">command</span>
<span class="k">def</span> <span class="nf">addGetfileToCommandList</span><span class="p">(</span><span class="n">filepath</span><span class="p">):</span>
<span class="n">command</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">command</span><span class="p">[</span><span class="s">'type'</span><span class="p">]</span> <span class="o">=</span> <span class="s">"GetFile"</span>
<span class="n">command</span><span class="p">[</span><span class="s">"params"</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">command</span><span class="p">[</span><span class="s">"params"</span><span class="p">].</span><span class="n">append</span><span class="p">({</span><span class="s">"key"</span><span class="p">:</span><span class="s">"Path"</span><span class="p">,</span><span class="s">"value"</span><span class="p">:</span><span class="n">filepath</span><span class="p">})</span>
<span class="k">return</span> <span class="n">command</span>
<span class="c1"># As simple example, if I wanted to look at the hosts DNS cache...
</span><span class="n">liveResponseCommands</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">liveResponseCommands</span><span class="p">[</span><span class="s">'Commands'</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
<span class="c1"># Add a command to run ipconfig and redirect to a file
</span><span class="n">command</span> <span class="o">=</span> <span class="n">addCmdToCommandList</span><span class="p">(</span><span class="s">"ipconfig /displaydns > c:\dnscache.txt"</span><span class="p">)</span>
<span class="n">liveResponseCommands</span><span class="p">[</span><span class="s">'Commands'</span><span class="p">].</span><span class="n">append</span><span class="p">(</span><span class="n">command</span><span class="p">)</span>
<span class="c1"># Add a command t collect the file's contents
</span><span class="n">command</span> <span class="o">=</span> <span class="n">addGetfileToCommandList</span><span class="p">(</span><span class="s">"c:\dnscache.txt"</span><span class="p">)</span>
<span class="n">liveResponseCommands</span><span class="p">[</span><span class="s">'Commands'</span><span class="p">].</span><span class="n">append</span><span class="p">(</span><span class="n">command</span><span class="p">)</span>
<span class="c1"># ALL LIVE RESPONSE REQUESTS MUST HAVE A COMMENT
</span><span class="n">liveResponseCommands</span><span class="p">[</span><span class="s">'Comment'</span><span class="p">]</span> <span class="o">=</span> <span class="s">"Collecting DNS cache"</span>
<span class="n">liveResponseCommands</span>
</code></pre></div></div>
<p>Output:</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>{
"Commands": [
{
"type": "RunScript",
"params": [
{
"key": "ScriptName",
"value": "cmd.ps1"
},
{
"key": "Args",
"value": "ipconfig /displaydns > c:\\dnscache.txt"
}
]
},
{
"type": "GetFile",
"params": [
{
"key": "Path",
"value": "c:\\dnscache.txt"
}
]
}
],
"Comment": "Collecting DNS cache"
}
</code></pre></div></div>
<h2 id="running-the-live-response-machine-action">Running the Live Response Machine Action</h2>
<p>To run this against a specific endpoint, grab the machine id and do something like this…</p>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">machineID</span> <span class="o">=</span> <span class="s">"796f7520617265207375706572206c616d652121"</span>
<span class="n">cmdRequest</span> <span class="o">=</span> <span class="n">MDErequest</span><span class="p">(</span><span class="s">"machines/%s/runliveresponse"</span> <span class="o">%</span> <span class="p">(</span><span class="n">machineID</span><span class="p">),</span><span class="n">liveResponseCommands</span><span class="p">)</span>
<span class="n">cmdRequest</span>
</code></pre></div></div>
<p>Output:</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>{'@odata.context': 'https://api.securitycenter.windows.com/api/$metadata#MachineActions/$entity',
'id': '944850f6-8043-4ca4-a65f-b50d0a1ea6c8',
'type': 'LiveResponse',
'title': None,
'requestor': 'JonathanGlass@HalfFullofSecurity.onmicrosoft.com',
'requestorComment': 'Collecting DNS cache',
'status': 'Pending',
'machineId': '796f7520617265207375706572206c616d652121',
'computerDnsName': 'desktop-l3mnbj9',
'creationDateTimeUtc': '2022-03-13T17:06:03.5759458Z',
'lastUpdateDateTimeUtc': '2022-03-13T17:06:03.5759458Z',
'cancellationRequestor': None,
'cancellationComment': None,
'cancellationDateTimeUtc': None,
'errorHResult': 0,
'scope': None,
'externalId': None,
'requestSource': 'PublicApi',
'relatedFileInfo': None,
'commands': [{'index': 0,
'startTime': None,
'endTime': None,
'commandStatus': 'Created',
'errors': [],
'command': {'type': 'RunScript',
'params': [{'key': 'ScriptName', 'value': 'cmd.ps1'},
{'key': 'Args', 'value': 'ipconfig /displaydns > c:\\dnscache.txt'}]}},
{'index': 1,
'startTime': None,
'endTime': None,
'commandStatus': 'Created',
'errors': [],
'command': {'type': 'GetFile',
'params': [{'key': 'Path', 'value': 'c:\\dnscache.txt'}]}}],
'troubleshootInfo': None}
</code></pre></div></div>
<h2 id="checking-the-status-of-the-live-response-machine-action">Checking the status of the Live Response Machine Action</h2>
<p>This one is pretty straightforward. Submit the ID you received from generating the machine action to the ol’ <strong>machineactions</strong> endpoint.</p>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">cmdStatus</span> <span class="o">=</span> <span class="n">MDErequest</span><span class="p">(</span><span class="s">"machineactions/%s"</span> <span class="o">%</span> <span class="p">(</span><span class="n">cmdRequest</span><span class="p">[</span><span class="s">'id'</span><span class="p">]))</span>
<span class="n">cmdStatus</span>
</code></pre></div></div>
<p>Output:</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>{'@odata.context': 'https://api.securitycenter.windows.com/api/$metadata#MachineActions/$entity',
'id': '944850f6-8043-4ca4-a65f-b50d0a1ea6c8',
'type': 'LiveResponse',
'title': None,
'requestor': 'JonathanGlass@HalfFullofSecurity.onmicrosoft.com',
'requestorComment': 'Collecting DNS cache',
'status': 'Pending',
'machineId': '796f7520617265207375706572206c616d652121',
'computerDnsName': 'desktop-l3mnbj9',
'creationDateTimeUtc': '2022-03-13T17:06:03.5759458Z',
'lastUpdateDateTimeUtc': '2022-03-13T17:06:18.480311Z',
'cancellationRequestor': None,
'cancellationComment': None,
'cancellationDateTimeUtc': None,
'errorHResult': 0,
'scope': None,
'externalId': None,
'requestSource': 'PublicApi',
'relatedFileInfo': None,
'commands': [{'index': 0,
'startTime': None,
'endTime': None,
'commandStatus': 'Created',
'errors': [],
'command': {'type': 'RunScript',
'params': [{'key': 'ScriptName', 'value': 'cmd.ps1'},
{'key': 'Args', 'value': 'ipconfig /displaydns > c:\\dnscache.txt'}]}},
{'index': 1,
'startTime': None,
'endTime': None,
'commandStatus': 'Created',
'errors': [],
'command': {'type': 'GetFile',
'params': [{'key': 'Path', 'value': 'c:\\dnscache.txt'}]}}],
'troubleshootInfo': None}
</code></pre></div></div>
<p>The machine action <strong>status</strong> field contains the current status of the command.
Possible values are: “Pending”, “InProgress”, “Succeeded”, “Failed”, “TimeOut”, and “Cancelled”.</p>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">cmdStatus</span> <span class="o">=</span> <span class="n">MDErequest</span><span class="p">(</span><span class="s">"machineactions/%s"</span> <span class="o">%</span> <span class="p">(</span><span class="n">cmdRequest</span><span class="p">[</span><span class="s">'id'</span><span class="p">]))</span>
<span class="n">cmdStatus</span>
</code></pre></div></div>
<p>Output:</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>{'@odata.context': 'https://api.securitycenter.windows.com/api/$metadata#MachineActions/$entity',
'id': '944850f6-8043-4ca4-a65f-b50d0a1ea6c8',
'type': 'LiveResponse',
'title': None,
'requestor': 'JonathanGlass@HalfFullofSecurity.onmicrosoft.com',
'requestorComment': 'Collecting DNS cache',
'status': 'Succeeded',
'machineId': '796f7520617265207375706572206c616d652121',
'computerDnsName': 'desktop-l3mnbj9',
'creationDateTimeUtc': '2022-03-13T17:06:03.5759458Z',
'lastUpdateDateTimeUtc': '2022-03-13T17:08:51.982182Z',
'cancellationRequestor': None,
'cancellationComment': None,
'cancellationDateTimeUtc': None,
'errorHResult': 0,
'scope': None,
'externalId': None,
'requestSource': 'PublicApi',
'relatedFileInfo': None,
'commands': [{'index': 0,
'startTime': '2022-03-13T17:08:24.28Z',
'endTime': '2022-03-13T17:08:28.003Z',
'commandStatus': 'Completed',
'errors': [],
'command': {'type': 'RunScript',
'params': [{'key': 'ScriptName', 'value': 'cmd.ps1'},
{'key': 'Args', 'value': 'ipconfig /displaydns > c:\\dnscache.txt'}]}},
{'index': 1,
'startTime': '2022-03-13T17:08:44.583Z',
'endTime': '2022-03-13T17:08:48.243Z',
'commandStatus': 'Completed',
'errors': [],
'command': {'type': 'GetFile',
'params': [{'key': 'Path', 'value': 'c:\\dnscache.txt'}]}}],
'troubleshootInfo': None}
</code></pre></div></div>
<h2 id="retrieving-the-contents-of-a-getfile-request">Retrieving the Contents of a GetFile Request</h2>
<p>When we leverage the <strong>GetLiveResponseResultDownloadLink</strong> endpoint, we can get the results of the commands we executed. Each command has an index. Since the GetFile command is index 1, we have to specify that in the result request.</p>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">liveResponseResult</span> <span class="o">=</span> <span class="n">MDErequest</span><span class="p">(</span><span class="s">"machineactions/%s/GetLiveResponseResultDownloadLink(index=1)"</span> <span class="o">%</span> <span class="p">(</span><span class="n">cmdStatus</span><span class="p">[</span><span class="s">'id'</span><span class="p">]))</span>
<span class="n">liveResponseResult</span>
</code></pre></div></div>
<p>Output:</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>{'@odata.context': 'https://api.securitycenter.windows.com/api/$metadata#Edm.String',
'value': 'https://ssus1westprod7.blob.core.windows.net/67e/78/sha256/767e78ee71556652fbdfa602a93645265ea0d6de583f38e047dac26367b1a3f2.zip?sv=2015-12-11&sr=b&sig=C1TdPqqYBLHpyoRM9Il1UMCewLjW9AuINMZnXitq6F4%3D&spr=https&st=2022-03-13T17%3A05%3A20Z&se=2022-03-13T17%3A40%3A20Z&sp=r&rscd=attachment%3B%20filename%3D%22dnscache.txt.gz%22'}
</code></pre></div></div>
<p>The files collected by GetFile are returned in a compressed format. Below is an example of how to decompress one in memory.</p>
<h2 id="decompressing-files-from-getfile-command">Decompressing Files from GetFile Command</h2>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="kn">import</span> <span class="nn">gzip</span>
<span class="kn">from</span> <span class="nn">io</span> <span class="kn">import</span> <span class="n">BytesIO</span>
<span class="n">response</span> <span class="o">=</span> <span class="n">requests</span><span class="p">.</span><span class="n">get</span><span class="p">(</span><span class="n">liveResponseResult</span><span class="p">[</span><span class="s">'value'</span><span class="p">])</span>
<span class="n">compressedFile</span> <span class="o">=</span> <span class="n">BytesIO</span><span class="p">(</span><span class="n">response</span><span class="p">.</span><span class="n">content</span><span class="p">)</span>
<span class="n">decompressedFile</span> <span class="o">=</span> <span class="n">gzip</span><span class="p">.</span><span class="n">GzipFile</span><span class="p">(</span><span class="n">fileobj</span><span class="o">=</span><span class="n">compressedFile</span><span class="p">)</span>
</code></pre></div></div>
<p>Since we know this is a file is going to be a unicode text file, we can view the contents like this..</p>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="k">print</span><span class="p">(</span><span class="n">decompressedFile</span><span class="p">.</span><span class="n">read</span><span class="p">().</span><span class="n">decode</span><span class="p">(</span><span class="s">'utf-16'</span><span class="p">).</span><span class="n">encode</span><span class="p">(</span><span class="s">'utf-8'</span><span class="p">).</span><span class="n">decode</span><span class="p">(</span><span class="s">'ascii'</span><span class="p">))</span>
</code></pre></div></div>
<p>Output:</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>Windows IP Configuration
automatedirstrprdeus3.blob.core.windows.net
----------------------------------------
Record Name . . . . . : automatedirstrprdeus3.blob.core.windows.net
Record Type . . . . . : 5
Time To Live . . . . : 57
Data Length . . . . . : 4
Section . . . . . . . : Answer
CNAME Record . . . . : blob.bnz10prdstr13a.store.core.windows.net
Record Name . . . . . : blob.bnz10prdstr13a.store.core.windows.net
Record Type . . . . . : 1
Time To Live . . . . : 57
Data Length . . . . . : 4
Section . . . . . . . : Answer
A (Host) Record . . . : 20.60.132.4
</code></pre></div></div>
<p>SUCCESS!!! I will show in the next post how to just read the STDOUT of a command from the Transcript but there maybe scenarios where you need to pipe the output of a command to file instead of STDOUT. Off the top of my head…
* Maybe your command takes longer that 10 minutes to run.
* Maybe your output is too large for the buffer Live Response is using to pull back STDOUT.</p>
<p>I am sure there are other reasons to send to a file instead of just reading the STDOUT manually.</p>
<h2 id="limitations-of-the-machine-action-api">Limitations of the Machine Action API</h2>
<ol>
<li>Rate limitations for this API are 10 calls per minute (additional requests are responded with HTTP 429).</li>
<li>25 concurrently running sessions (requests exceeding the throttling limit will receive a “429 - Too many requests” response).</li>
<li>If the machine is not available, the session will be queued for up to 3 days.</li>
<li>RunScript command timeouts after 10 minutes.</li>
<li>Live response commands cannot be queued up and can only be executed one at a time.</li>
<li>If the machine that you are trying to run this API call is in an RBAC device group that does not have an automated remediation level assigned to it, you’ll need to at least enable the minimum Remediation Level for a given Device Group.</li>
<li>Multiple live response commands can be run on a single API call. However, when a live response command fails all the subsequent actions will not be executed.</li>
<li>Parameters are a pain in the ass to encode across PowerShell and Batch it is probably best to stick with Powershell</li>
</ol>
<h2 id="references">References</h2>
<ul>
<li><a href="https://docs.microsoft.com/en-us/microsoft-365/security/defender-endpoint/run-live-response?view=o365-worldwide">https://docs.microsoft.com/en-us/microsoft-365/security/defender-endpoint/run-live-response?view=o365-worldwide</a></li>
</ul>Microsoft 365 Security: Kernel Level Access with Live Response2022-03-13T17:33:28+00:002022-03-13T17:33:28+00:00https://jon.glass/blog/Live-Response-Kernel-Access<p>There are times when security is annoying. As an example, when the Administrator account or even the SYSTEM account cannot access a file due to restrictions against accessing volume artifacts.</p>
<p><img src="data:image/png;base64, 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alt="Screenshot" /></p>
<p>For more about that command, check out <a href="https://jon.glass/adfirwmc/Ch2/">this post</a>.</p>
<h2 id="microsoft-defender-live-response-can-access-what-other-methods-cant">Microsoft Defender Live Response can access what other methods can’t</h2>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">liveResponseCommands</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">liveResponseCommands</span><span class="p">[</span><span class="s">'Commands'</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">command</span> <span class="o">=</span> <span class="n">addCmdToCommandList</span><span class="p">(</span><span class="s">"fsutil file queryextents \$LogFile"</span><span class="p">)</span>
<span class="n">liveResponseCommands</span><span class="p">[</span><span class="s">'Commands'</span><span class="p">].</span><span class="n">append</span><span class="p">(</span><span class="n">command</span><span class="p">)</span>
<span class="c1"># ALL LIVE RESPONSE REQUESTS MUST HAVE A COMMENT
</span><span class="n">liveResponseCommands</span><span class="p">[</span><span class="s">'Comment'</span><span class="p">]</span> <span class="o">=</span> <span class="s">"Looking at the LogFile clusters"</span>
<span class="n">machineID</span> <span class="o">=</span> <span class="s">"c6993a6c004946bf52d2d59237c18e6db4db7e5e"</span>
<span class="n">cmdRequest</span> <span class="o">=</span> <span class="n">MDErequest</span><span class="p">(</span><span class="s">"machines/%s/runliveresponse"</span> <span class="o">%</span> <span class="p">(</span><span class="n">machineID</span><span class="p">),</span><span class="n">liveResponseCommands</span><span class="p">)</span>
<span class="n">cmdStatus</span> <span class="o">=</span> <span class="n">MDErequest</span><span class="p">(</span><span class="s">"machineactions/%s"</span> <span class="o">%</span> <span class="p">(</span><span class="n">cmdRequest</span><span class="p">[</span><span class="s">'id'</span><span class="p">]))</span>
<span class="n">cmdStatus</span>
</code></pre></div></div>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>{'@odata.context': 'https://api.securitycenter.windows.com/api/$metadata#MachineActions/$entity',
'id': '440d4647-77ab-44d4-8039-1d1a566ddc51',
'type': 'LiveResponse',
'title': None,
'requestor': 'JonathanGlass@HalfFullofSecurity.onmicrosoft.com',
'requestorComment': 'Looking at the LogFile clusters',
'status': 'Succeeded',
'machineId': 'c6993a6c004946bf52d2d59237c18e6db4db7e5e',
'computerDnsName': 'desktop-l3mnbj9',
'creationDateTimeUtc': '2022-03-15T00:08:46.0251352Z',
'lastUpdateDateTimeUtc': '2022-03-15T00:09:40.247371Z',
'cancellationRequestor': None,
'cancellationComment': None,
'cancellationDateTimeUtc': None,
'errorHResult': 0,
'scope': None,
'externalId': None,
'requestSource': 'PublicApi',
'relatedFileInfo': None,
'commands': [{'index': 0,
'startTime': '2022-03-15T00:09:33.187Z',
'endTime': '2022-03-15T00:09:36.83Z',
'commandStatus': 'Completed',
'errors': [],
'command': {'type': 'RunScript',
'params': [{'key': 'ScriptName', 'value': 'cmd.ps1'},
{'key': 'Args', 'value': 'fsutil file queryextents \\$LogFile'}]}}],
'troubleshootInfo': None}
</code></pre></div></div>
<h2 id="how-to-print-the-stdout-of-a-command-run-from-live-response">How to Print the STDOUT of a Command Run from Live Response</h2>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">liveResponseResult</span> <span class="o">=</span> <span class="n">MDErequest</span><span class="p">(</span><span class="s">"machineactions/%s/GetLiveResponseResultDownloadLink(index=0)"</span> <span class="o">%</span> <span class="p">(</span><span class="n">cmdStatus</span><span class="p">[</span><span class="s">'id'</span><span class="p">]))</span>
<span class="n">response</span> <span class="o">=</span> <span class="n">requests</span><span class="p">.</span><span class="n">get</span><span class="p">(</span><span class="n">liveResponseResult</span><span class="p">[</span><span class="s">'value'</span><span class="p">])</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">response</span><span class="p">.</span><span class="n">content</span><span class="p">.</span><span class="n">decode</span><span class="p">(</span><span class="s">'utf8'</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">json</span><span class="p">.</span><span class="n">loads</span><span class="p">(</span><span class="n">data</span><span class="p">)[</span><span class="s">'script_output'</span><span class="p">])</span>
</code></pre></div></div>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>Transcript started, output file is C:\ProgramData\Microsoft\Windows Defender Advanced Threat Protection\Temp\PSScriptOutputs\PSScript_Transcript_{03C57FC2-BA2C-4112-BC38-B9DD9EBE6A71}.txt
VCN: 0x0 Clusters: 0x1 LCN: 0x2c
VCN: 0x1 Clusters: 0x1 LCN: 0x500e29
</code></pre></div></div>
<p>Boom. Live Response’s access to the kernel allows for access that is unavailable at the command line.</p>Microsoft 365 Security: Using the API for Live Response2022-03-10T17:33:28+00:002022-03-10T17:33:28+00:00https://jon.glass/blog/MDE-Live-Response-via-API<h2 id="adding-a-file-to-the-mde-live-response-library-and-running-it-on-an-endpoint">Adding a file to the MDE Live Response Library and Running it on an Endpoint</h2>
<p>Continuing to build on my previous posts…</p>
<p>One of my all time favorite user containment methods is to change the BitLocker keys and shut the system down.</p>
<div class="language-powershell highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="c">#Delete existing protections</span><span class="w">
</span><span class="n">manage-bde.exe</span><span class="w"> </span><span class="nt">-protectors</span><span class="w"> </span><span class="nt">-delete</span><span class="w"> </span><span class="nx">c:</span><span class="w"> </span><span class="nt">-Type</span><span class="w"> </span><span class="nx">TPMAndPIN</span><span class="w">
</span><span class="n">manage-bde.exe</span><span class="w"> </span><span class="nt">-protectors</span><span class="w"> </span><span class="nt">-delete</span><span class="w"> </span><span class="nx">c:</span><span class="w"> </span><span class="nt">-Type</span><span class="w"> </span><span class="nx">RecoveryPassword</span><span class="w">
</span><span class="c">#Now that all of the previous Protectors are gone, let's add our own.</span><span class="w">
</span><span class="c">#Let's add a new password that only the security team will need to know.</span><span class="w">
</span><span class="n">manage-bde.exe</span><span class="w"> </span><span class="nt">-protectors</span><span class="w"> </span><span class="nt">-add</span><span class="w"> </span><span class="nx">c:</span><span class="w"> </span><span class="nt">-TPMandPIN</span><span class="w"> </span><span class="nx">SuperDuperPassword</span><span class="w">
</span><span class="c">#As a backup, let's also add a couple of recovery keys</span><span class="w">
</span><span class="n">manage-bde.exe</span><span class="w"> </span><span class="nt">-protectors</span><span class="w"> </span><span class="nt">-add</span><span class="w"> </span><span class="nx">c:</span><span class="w"> </span><span class="nt">-RecoveryPassword</span><span class="w"> </span><span class="nx">111111-111111-111111-111111-111111-111111-111111-111111</span><span class="w">
</span><span class="n">manage-bde.exe</span><span class="w"> </span><span class="nt">-protectors</span><span class="w"> </span><span class="nt">-add</span><span class="w"> </span><span class="nx">c:</span><span class="w"> </span><span class="nt">-RecoveryPassword</span><span class="w"> </span><span class="nx">222222-222222-222222-222222-222222-222222-222222-222222</span><span class="w">
</span><span class="n">manage-bde.exe</span><span class="w"> </span><span class="nt">-on</span><span class="w"> </span><span class="nx">c:</span><span class="w">
</span><span class="n">shutdown</span><span class="w"> </span><span class="nx">/f</span><span class="w"> </span><span class="nx">/s</span><span class="w"> </span><span class="nx">/t</span><span class="w"> </span><span class="nx">0</span><span class="w">
</span></code></pre></div></div>
<h2 id="making-a-function-to-post-library-files">Making a function to Post Library Files</h2>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code>
<span class="k">def</span> <span class="nf">postFileToLiveResponseLibrary</span><span class="p">(</span><span class="n">fileObjToUpload</span><span class="p">,</span> <span class="n">description</span><span class="p">,</span> <span class="n">parameters</span><span class="o">=</span><span class="s">""</span><span class="p">,</span> <span class="n">override</span> <span class="o">=</span> <span class="bp">False</span><span class="p">,</span> <span class="n">token</span><span class="o">=</span><span class="n">result</span><span class="p">[</span><span class="s">"access_token"</span><span class="p">]):</span>
<span class="n">headers</span> <span class="o">=</span> <span class="p">{</span><span class="s">'Authorization'</span> <span class="p">:</span> <span class="s">"Bearer "</span> <span class="o">+</span> <span class="n">token</span> <span class="p">}</span>
<span class="n">url</span> <span class="o">=</span> <span class="s">"https://api.securitycenter.windows.com/api/libraryfiles"</span>
<span class="n">files</span><span class="o">=</span><span class="p">{</span><span class="s">'file'</span><span class="p">:</span> <span class="n">fileObjToUpload</span><span class="p">}</span>
<span class="n">params</span><span class="o">=</span><span class="p">{</span>
<span class="s">'Description'</span><span class="p">:</span> <span class="n">description</span><span class="p">,</span>
<span class="s">'ParametersDescription'</span><span class="p">:</span> <span class="n">parameters</span><span class="p">,</span>
<span class="s">'OverrideIfExists'</span><span class="p">:</span><span class="n">override</span>
<span class="p">}</span>
<span class="n">response</span> <span class="o">=</span> <span class="n">requests</span><span class="p">.</span><span class="n">post</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">params</span><span class="p">,</span> <span class="n">files</span><span class="o">=</span><span class="n">files</span><span class="p">,</span> <span class="n">headers</span><span class="o">=</span><span class="n">headers</span><span class="p">,</span> <span class="n">verify</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<span class="k">return</span> <span class="n">response</span><span class="p">.</span><span class="n">json</span><span class="p">()</span>
</code></pre></div></div>
<h2 id="adding-a-containment-script-to-your-live-response-library">Adding a Containment Script to Your Live Response Library</h2>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="kn">from</span> <span class="nn">io</span> <span class="kn">import</span> <span class="n">StringIO</span>
<span class="n">script</span> <span class="o">=</span> <span class="s">"""
#Delete existing protections
manage-bde.exe -protectors -delete c: -Type TPMAndPIN
manage-bde.exe -protectors -delete c: -Type RecoveryPassword
#Now that all of the previous Protectors are gone, let's add our own.
#Let's add a new password that only the security team will need to know.
manage-bde.exe -protectors -add c: -TPMandPIN SuperDuperPassword
#As a backup, let's also add a couple of recovery keys
manage-bde.exe -protectors -add c: -RecoveryPassword 111111-111111-111111-111111-111111-111111-111111-111111
manage-bde.exe -protectors -add c: -RecoveryPassword 222222-222222-222222-222222-222222-222222-222222-222222
manage-bde.exe -on c:
"""</span>
<span class="c1">#StringIO is a fun module that lets you treat strings like file objects.
</span><span class="n">fileobj</span> <span class="o">=</span> <span class="n">StringIO</span><span class="p">(</span><span class="n">script</span><span class="p">)</span>
<span class="n">fileobj</span><span class="p">.</span><span class="n">filename</span> <span class="o">=</span> <span class="s">"contain.ps1"</span>
<span class="n">postFileToLiveResponseLibrary</span><span class="p">(</span>
<span class="n">fileObjToUpload</span> <span class="o">=</span> <span class="n">fileobj</span><span class="p">,</span>
<span class="n">description</span> <span class="o">=</span> <span class="s">"BitLocker Containment Script"</span><span class="p">,</span>
<span class="n">parameters</span> <span class="o">=</span> <span class="s">"Parameter Info Would Go Here"</span><span class="p">,</span>
<span class="n">override</span> <span class="o">=</span> <span class="bp">True</span>
<span class="p">)</span>
</code></pre></div></div>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>{'@odata.context': 'https://api.securitycenter.windows.com/api/$metadata#LibraryFiles/$entity',
'fileName': 'file',
'sha256': '8052835f7fcbca7b123e763b3e429f552cda4d6d3ddcf193d4b356ca01b9e7b4',
'description': 'BitLocker Containment Script',
'creationTime': '2022-03-10T13:35:27.841749Z',
'lastUpdatedTime': '2022-03-10T13:35:27.841749Z',
'createdBy': 'Jonathan Glass',
'hasParameters': False,
'parametersDescription': 'Parameter Info Would Go Here'}
</code></pre></div></div>
<p>Sweet! It worked!</p>
<h2 id="running-your-newly-uploaded-script-against-an-endpoint">Running your newly uploaded script against an endpoint</h2>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">liveResponseCommands</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">liveResponseCommands</span><span class="p">[</span><span class="s">'Commands'</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">command</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">command</span><span class="p">[</span><span class="s">'type'</span><span class="p">]</span> <span class="o">=</span> <span class="s">"RunScript"</span>
<span class="n">command</span><span class="p">[</span><span class="s">"params"</span><span class="p">]</span> <span class="o">=</span> <span class="p">[{</span><span class="s">"key"</span><span class="p">:</span><span class="s">"ScriptName"</span><span class="p">,</span>
<span class="s">"value"</span><span class="p">:</span><span class="s">"contain.ps1"</span><span class="p">}]</span>
<span class="n">liveResponseCommands</span><span class="p">[</span><span class="s">'Commands'</span><span class="p">].</span><span class="n">append</span><span class="p">(</span><span class="n">command</span><span class="p">)</span>
<span class="n">liveResponseCommands</span><span class="p">[</span><span class="s">'Comment'</span><span class="p">]</span> <span class="o">=</span> <span class="s">"Containing Endpoint via BitLocker"</span>
<span class="n">liveResponseCommands</span>
</code></pre></div></div>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>{'Commands': [{'type': 'RunScript',
'params': [{'key': 'ScriptName', 'value': 'contain.ps1'}]}],
'Comment': 'Containing Endpoint via BitLocker'}
</code></pre></div></div>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">machineID</span> <span class="o">=</span> <span class="s">"c6993a6c004946bf52d2d59237c18e6db4db7e5e"</span>
<span class="n">MDErequest</span><span class="p">(</span><span class="s">"machines/%s/runliveresponse"</span> <span class="o">%</span> <span class="p">(</span><span class="n">machineID</span><span class="p">),</span>
<span class="n">liveResponseCommands</span><span class="p">)</span>
</code></pre></div></div>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>{'@odata.context': 'https://api.securitycenter.windows.com/api/$metadata#MachineActions/$entity',
'id': '9509426d-490c-4f2b-90b4-4703674be8cf',
'type': 'LiveResponse',
'title': None,
'requestor': 'JonathanGlass@HalfFullofSecurity.onmicrosoft.com',
'requestorComment': 'Containing Endpoint via BitLocker',
'status': 'Pending',
'machineId': 'c6993a62004946bf52d2d59237c18e6db4db7e5e',
'computerDnsName': 'desktop-l3mnbj9',
'creationDateTimeUtc': '2022-03-10T14:36:51.8759111Z',
'lastUpdateDateTimeUtc': '2022-03-10T14:36:51.8759111Z',
'cancellationRequestor': None,
'cancellationComment': None,
'cancellationDateTimeUtc': None,
'errorHResult': 0,
'scope': None,
'externalId': None,
'requestSource': 'PublicApi',
'relatedFileInfo': None,
'commands': [{'index': 0,
'startTime': None,
'endTime': None,
'commandStatus': 'Created',
'errors': [],
'command': {'type': 'RunScript',
'params': [{'key': 'ScriptName', 'value': 'contain.ps1'}]}}],
'troubleshootInfo': None}
</code></pre></div></div>
<h2 id="deleting-a-file-from-your-live-response-library">Deleting a file from your Live Response Library</h2>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="k">def</span> <span class="nf">deleteFileFromLiveResponseLibrary</span><span class="p">(</span><span class="n">filename</span><span class="p">,</span> <span class="n">token</span><span class="o">=</span><span class="n">result</span><span class="p">[</span><span class="s">"access_token"</span><span class="p">]):</span>
<span class="n">headers</span> <span class="o">=</span> <span class="p">{</span><span class="s">'Authorization'</span> <span class="p">:</span> <span class="s">"Bearer "</span> <span class="o">+</span> <span class="n">token</span> <span class="p">}</span>
<span class="n">url</span> <span class="o">=</span> <span class="s">"https://api.securitycenter.windows.com/api/libraryfiles/%s"</span> <span class="o">%</span> <span class="p">(</span><span class="n">filename</span><span class="p">)</span>
<span class="n">response</span> <span class="o">=</span> <span class="n">requests</span><span class="p">.</span><span class="n">delete</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">headers</span><span class="o">=</span><span class="n">headers</span><span class="p">,</span> <span class="n">verify</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<span class="k">return</span> <span class="n">response</span>
<span class="n">deleteFileFromLiveResponseLibrary</span><span class="p">(</span><span class="s">"contain.ps1"</span><span class="p">)</span>
</code></pre></div></div>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code><Response [204]> means it worked!
</code></pre></div></div>Microsoft 365 Security: Building a quick API wrapper2022-03-09T17:33:28+00:002022-03-09T17:33:28+00:00https://jon.glass/blog/Building-API-Wrapper<h2 id="building-a-wrapper-for-mde-interactions">Building a Wrapper for MDE interactions</h2>
<p>My goal here is to reduce the amount of redundant code needed to query Microsoft Defender for Endpoint. This is not fault tolerent or comprehensive. Just something quick to save keystrokes.
This is a continuation of the previous post.</p>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="k">def</span> <span class="nf">MDErequest</span><span class="p">(</span><span class="n">uri</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="s">""</span><span class="p">,</span> <span class="n">token</span><span class="o">=</span><span class="n">result</span><span class="p">[</span><span class="s">"access_token"</span><span class="p">]):</span>
<span class="n">headers</span> <span class="o">=</span> <span class="p">{</span>
<span class="s">'Content-Type'</span> <span class="p">:</span> <span class="s">'application/json'</span><span class="p">,</span>
<span class="s">'Accept'</span> <span class="p">:</span> <span class="s">'application/json'</span><span class="p">,</span>
<span class="s">'Authorization'</span> <span class="p">:</span> <span class="s">"Bearer "</span> <span class="o">+</span> <span class="n">token</span>
<span class="p">}</span>
<span class="n">url</span> <span class="o">=</span> <span class="s">"https://api.securitycenter.windows.com/api/%s"</span> <span class="o">%</span> <span class="p">(</span><span class="n">uri</span><span class="p">)</span>
<span class="k">if</span> <span class="n">data</span><span class="p">:</span>
<span class="n">response</span> <span class="o">=</span> <span class="n">requests</span><span class="p">.</span><span class="n">post</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">json</span><span class="o">=</span><span class="n">data</span><span class="p">,</span> <span class="n">headers</span><span class="o">=</span><span class="n">headers</span><span class="p">,</span> <span class="n">verify</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">response</span> <span class="o">=</span> <span class="n">requests</span><span class="p">.</span><span class="n">get</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">headers</span><span class="o">=</span><span class="n">headers</span><span class="p">,</span> <span class="n">verify</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<span class="k">return</span> <span class="n">response</span><span class="p">.</span><span class="n">json</span><span class="p">()</span>
</code></pre></div></div>
<h2 id="using-the-api-to-review-mde-alerts">Using the API to Review MDE Alerts</h2>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">queryResponse</span> <span class="o">=</span> <span class="n">MDErequest</span><span class="p">(</span><span class="s">"alerts"</span><span class="p">)</span>
<span class="n">queryResponse</span><span class="p">[</span><span class="s">'value'</span><span class="p">]</span>
</code></pre></div></div>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>[{'id': 'da637821323029223838_-1136569686',
'incidentId': 1,
'investigationId': None,
'assignedTo': None,
'severity': 'Informational',
'status': 'New',
'classification': None,
'determination': None,
'investigationState': 'UnsupportedOs',
'detectionSource': 'WindowsDefenderAtp',
'detectorId': '22222222-2222-2222-2222-222222222222',
'category': 'Execution',
'threatFamilyName': None,
'title': '[Test Alert] Suspicious Powershell commandline',
'description': ' This is a test alert \nA suspicious Powershell commandline was found on the machine. This commandline might be used during installation, exploration, or in some cases with lateral movement activities which are used by attackers to invoke modules, download external payloads, and get more information about the system. Attackers usually use Powershell to bypass security protection mechanisms by executing their payload in memory without touching the disk and leaving any trace.',
'alertCreationTime': '2022-03-06T02:58:22.9224109Z',
'firstEventTime': '2022-03-06T02:40:56.1886556Z',
'lastEventTime': '2022-03-06T02:40:56.1886556Z',
'lastUpdateTime': '2022-03-06T02:58:24.0466667Z',
'resolvedTime': None,
'machineId': 'c6993a6c004246bf52d2d59237c18e6db4db7e5e',
'computerDnsName': 'desktop-l3mnbj9',
'rbacGroupName': None,
'aadTenantId': '11111111-1111-1111-1111-111111111111',
'threatName': None,
'mitreTechniques': ['T1059.001'],
'relatedUser': {'userName': 'Glass', 'domainName': 'DESKTOP-L3MNBJ9'},
'loggedOnUsers': [{'accountName': 'Glass', 'domainName': 'DESKTOP-L3MNBJ9'}],
'comments': [],
'evidence': []}]
</code></pre></div></div>
<h2 id="using-the-api-to-do-advanced-threat-hunting">Using the API to do Advanced Threat Hunting</h2>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">query</span> <span class="o">=</span> <span class="p">{</span><span class="s">'Query'</span> <span class="p">:</span><span class="s">"""DeviceProcessEvents | where InitiatingProcessFileName =~ </span><span class="se">\"</span><span class="s">powershell.exe</span><span class="se">\"</span><span class="s">
| project Timestamp, FileName, InitiatingProcessCommandLine
| order by Timestamp desc
| limit 1"""</span> <span class="p">}</span>
<span class="n">queryResponse</span> <span class="o">=</span> <span class="n">MDErequest</span><span class="p">(</span><span class="s">"advancedqueries/run"</span><span class="p">,</span> <span class="n">query</span><span class="p">)</span>
<span class="n">queryResponse</span><span class="p">[</span><span class="s">'Results'</span><span class="p">]</span>
</code></pre></div></div>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>[{'Timestamp': '2022-03-10T14:03:13.1151059Z',
'FileName': 'WerFault.exe',
'InitiatingProcessCommandLine': 'powershell.exe -ExecutionPolicy AllSigned -NoProfile -NonInteractive -Command "& {$OutputEncoding = [Console]::OutputEncoding =[System.Text.Encoding]::UTF8;$scriptFileStream = [System.IO.File]::Open(\'C:\\ProgramData\\Microsoft\\Windows Defender Advanced Threat Protection\\DataCollection\\8099.7011103.0.7008675-77a99c323dc18f055614eedeb6e307c388905ec9\\0e3d6d2d-06cc-486d-9465-9ef3bee75444.ps1\', [System.IO.FileMode]::Open, [System.IO.FileAccess]::Read, [System.IO.FileShare]::Read);$calculatedHash = Get-FileHash \'C:\\ProgramData\\Microsoft\\Windows Defender Advanced Threat Protection\\DataCollection\\8099.7011103.0.7008675-77a99c323dc18f055614eedeb6e307c388905ec9\\0e3d6d2d-06cc-486d-9465-9ef3bee75444.ps1\' -Algorithm SHA256;if (!($calculatedHash.Hash -eq \'29a688ce6549a06fb576fec79422f6f6882265e0f674ab3b4c3ceb8f83aec9d3\')) { exit 323;}; . \'C:\\ProgramData\\Microsoft\\Windows Defender Advanced Threat Protection\\DataCollection\\8099.7011103.0.7008675-77a99c323dc18f055614eedeb6e307c388905ec9\\0e3d6d2d-06cc-486d-9465-9ef3bee75444.ps1\' }"'}]
</code></pre></div></div>
<p>Easy Peasy.</p>Microsoft 365 Security: Multifactor API Access2022-03-06T17:33:28+00:002022-03-06T17:33:28+00:00https://jon.glass/blog/MDEAPIMFA<p>I have decided to dust off the ol’ blog to start documenting some of my more recent endeavors leveraging the Microsoft 365 Security suite to perform Incident Response. Since I prefer to talk to APIs more than people, this seemed like a good opportunity to explore the different components of the ecosystem through the language of Python. Generic instructions are being provided to get you started but there are a lot of nuances with the environment and I can’t bring myself to document them all.</p>
<h2 id="getting-started">Getting Started</h2>
<ol>
<li>Go <a href="https://docs.microsoft.com/en-us/microsoft-365/security/defender-endpoint/evaluate-mde?view=o365-worldwide">here</a> and get yourself a free 3 month license for Defender for Endpoint</li>
<li>Click next and agree until it stops asking. Literally have no clue what I agreed to.</li>
<li>Go to <a href="https://security.microsoft.com/homepage">Microsoft 365 Defender</a>.</li>
<li>Go to <strong>Settings > Endpoints > Onboarding</strong>, grab an onboarding script, and onboard a device to your environment. <a href="https://docs.microsoft.com/en-us/microsoft-365/security/defender-endpoint/onboard-configure?view=o365-worldwide">Reference</a></li>
<li>Reboot the device. You shouldn’t have to but it makes every thing go faster.</li>
<li>Head to <a href="https://portal.azure.com/#blade/Microsoft_AAD_RegisteredApps/ApplicationsListBlade">Azure</a> and build yourself and App.</li>
<li>Go to <strong>YOUR APP > Certificates & secrets</strong> and make yourself a New client secret. Copy that down because you can only look at that once. We will need that later.</li>
<li>Go to <strong>YOUR APP > API Permissions</strong> and Click Add a Permission.</li>
<li>When the <strong>Request API permissions</strong> side screen pops up, click on <strong>APIs my organization uses</strong>. Type <strong>“WindowsDefenderATP”</strong> in the search box.</li>
<li>Click on <strong>Application permissions</strong> Select EVERYTHING. Go nuts. Hit <strong>Update Permissions</strong></li>
<li>Now before you click away, Click <strong>Grant admin consent to YOUR DOMAIN</strong>. This should turn all orange “Not granted for”s into green “Granted for”s.</li>
<li>Go to the <strong>YOUR APP > Overview</strong> page and gather your <strong>Application (client) ID</strong> and <strong>Directory (tenant) ID</strong>. We will need the <strong>Tenent ID</strong>, <strong>App ID</strong>, and <strong>Client Secret</strong> to play with the API.</li>
<li>Go to <strong>YOUR APP > Authentication</strong> page and under Platform configurations:
<ul>
<li>Click <strong>Add Platform</strong></li>
<li>Click <strong>Web</strong></li>
<li>Add https://portal.azure.com as a <strong>Redirect URI</strong></li>
</ul>
</li>
<li>Navigate over to <strong><a href="https://portal.azure.com/#blade/Microsoft_AAD_IAM/ConditionalAccessBlade/ClassicPolicies">Conditional Access > Classic policies</a></strong> and disable that <strong>[Windows Defender ATP] Device policy</strong> or…you know, join your computer to this Domain. Your call.</li>
</ol>
<p>Those are the rough strokes. Is it more complicated than that? Yes. I encourage everyone to RTFMs from Microsoft on spinning up a new M365.</p>
<h2 id="getting-an-auth-token">Getting an Auth Token</h2>
<p>To talk to the API, we will be leveraging the msal module to query Graph while changing the scope to Microsoft Defender for Endpoint’s API. This is the product of a lot of trial and error BUT the benefit of this is to multifactor the API so we can leverage the API via Jupyter Notebooks without having secret keys laying around everywhere.</p>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="kn">import</span> <span class="nn">msal</span>
<span class="kn">import</span> <span class="nn">json</span>
<span class="kn">import</span> <span class="nn">requests</span>
<span class="kn">from</span> <span class="nn">datetime</span> <span class="kn">import</span> <span class="n">datetime</span>
<span class="kn">from</span> <span class="nn">msal_extensions</span> <span class="kn">import</span> <span class="o">*</span>
<span class="kn">import</span> <span class="nn">urllib3</span>
<span class="n">urllib3</span><span class="p">.</span><span class="n">disable_warnings</span><span class="p">()</span>
<span class="n">tenantID</span> <span class="o">=</span> <span class="s">'11111111-1111-1111-1111-111111111111'</span>
<span class="n">clientID</span> <span class="o">=</span> <span class="s">'22222222-2222-2222-2222-222222222222'</span>
<span class="n">authority</span> <span class="o">=</span> <span class="s">'https://login.microsoftonline.com/'</span> <span class="o">+</span> <span class="n">tenantID</span>
<span class="n">scope</span> <span class="o">=</span> <span class="p">[</span><span class="s">"https://api.securitycenter.microsoft.com/AdvancedQuery.Read"</span><span class="p">]</span>
<span class="n">username</span> <span class="o">=</span> <span class="s">'JonathanGlass@HalfFullofSecurity.onmicrosoft.com'</span>
<span class="n">result</span> <span class="o">=</span> <span class="bp">None</span>
<span class="n">tokenExpiry</span> <span class="o">=</span> <span class="bp">None</span>
<span class="k">def</span> <span class="nf">msal_delegated_device_flow</span><span class="p">(</span><span class="n">clientID</span><span class="p">,</span> <span class="n">scope</span><span class="p">,</span> <span class="n">authority</span><span class="p">):</span>
<span class="k">print</span><span class="p">(</span><span class="s">"Initiate Device Code Flow to get an AAD Access Token."</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="s">"Open a browser window and paste in the URL below and then enter the Code. CTRL+C to cancel."</span><span class="p">)</span>
<span class="n">app</span> <span class="o">=</span> <span class="n">msal</span><span class="p">.</span><span class="n">PublicClientApplication</span><span class="p">(</span><span class="n">client_id</span><span class="o">=</span><span class="n">clientID</span><span class="p">,</span> <span class="n">authority</span><span class="o">=</span><span class="n">authority</span><span class="p">)</span>
<span class="n">flow</span> <span class="o">=</span> <span class="n">app</span><span class="p">.</span><span class="n">initiate_device_flow</span><span class="p">(</span><span class="n">scopes</span><span class="o">=</span><span class="n">scope</span><span class="p">)</span>
<span class="k">if</span> <span class="s">"user_code"</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">flow</span><span class="p">:</span>
<span class="k">raise</span> <span class="nb">ValueError</span><span class="p">(</span><span class="s">"Fail to create device flow. Err: %s"</span> <span class="o">%</span> <span class="n">json</span><span class="p">.</span><span class="n">dumps</span><span class="p">(</span><span class="n">flow</span><span class="p">,</span> <span class="n">indent</span><span class="o">=</span><span class="mi">4</span><span class="p">))</span>
<span class="k">print</span><span class="p">(</span><span class="n">flow</span><span class="p">[</span><span class="s">"message"</span><span class="p">])</span>
<span class="n">result</span> <span class="o">=</span> <span class="n">app</span><span class="p">.</span><span class="n">acquire_token_by_device_flow</span><span class="p">(</span><span class="n">flow</span><span class="p">)</span>
<span class="k">return</span> <span class="n">result</span>
<span class="c1"># Get a new Access Token using the Device Code Flow
</span><span class="n">result</span> <span class="o">=</span> <span class="n">msal_delegated_device_flow</span><span class="p">(</span><span class="n">clientID</span><span class="p">,</span> <span class="n">scope</span><span class="p">,</span> <span class="n">authority</span><span class="p">)</span>
<span class="k">if</span> <span class="n">result</span><span class="p">[</span><span class="s">"access_token"</span><span class="p">]:</span>
<span class="k">print</span><span class="p">(</span><span class="s">"We have a Token!"</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="s">"access_token"</span><span class="p">][:</span><span class="mi">100</span><span class="p">]</span><span class="o">+</span><span class="s">"..."</span><span class="p">)</span>
</code></pre></div></div>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>Initiate Device Code Flow to get an AAD Access Token.
Open a browser window and paste in the URL below and then enter the Code. CTRL+C to cancel.
To sign in, use a web browser to open the page https://microsoft.com/devicelogin and enter the code R8H6RUBCH to authenticate.
We have a Token!
eyJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiIsIng1dCI6ImpTMVhvMU9XRGpfNTJ2YndHTmd2UU8yVnpNYyIsImtpZCI6ImpTMVhv...
</code></pre></div></div>
<h3 id="what-is-in-this-token">What is in this token?</h3>
<p>This authentication request returns a <a href="https://en.wikipedia.org/wiki/JSON_Web_Token">JSON Web Token</a>.
A couple of JSON objects and a binary signature at the end. Decoded the main part looks like this</p>
<div class="language-json highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="p">{</span><span class="w">
</span><span class="nl">"aud"</span><span class="p">:</span><span class="w"> </span><span class="s2">"https://api.securitycenter.microsoft.com"</span><span class="p">,</span><span class="w">
</span><span class="nl">"iss"</span><span class="p">:</span><span class="w"> </span><span class="s2">"https://sts.windows.net/11111111-1111-1111-1111-111111111111/"</span><span class="p">,</span><span class="w">
</span><span class="nl">"iat"</span><span class="p">:</span><span class="w"> </span><span class="mi">1646594420</span><span class="p">,</span><span class="w">
</span><span class="nl">"nbf"</span><span class="p">:</span><span class="w"> </span><span class="mi">1646594420</span><span class="p">,</span><span class="w">
</span><span class="nl">"exp"</span><span class="p">:</span><span class="w"> </span><span class="mi">1646598320</span><span class="p">,</span><span class="w">
</span><span class="nl">"aio"</span><span class="p">:</span><span class="w"> </span><span class="s2">"E2ZgYJgYsw2fBq9T2rVW7Xu8R/3NqgBQA="</span><span class="p">,</span><span class="w">
</span><span class="nl">"app_displayname"</span><span class="p">:</span><span class="w"> </span><span class="s2">"API for MDE"</span><span class="p">,</span><span class="w">
</span><span class="nl">"appid"</span><span class="p">:</span><span class="w"> </span><span class="s2">"33333333-3333-3333-3333-333333333333"</span><span class="p">,</span><span class="w">
</span><span class="nl">"appidacr"</span><span class="p">:</span><span class="w"> </span><span class="s2">"1"</span><span class="p">,</span><span class="w">
</span><span class="nl">"idp"</span><span class="p">:</span><span class="w"> </span><span class="s2">"https://sts.windows.net/11111111-1111-1111-1111-111111111111/"</span><span class="p">,</span><span class="w">
</span><span class="nl">"oid"</span><span class="p">:</span><span class="w"> </span><span class="s2">"22222222-2222-2222-2222-222222222222"</span><span class="p">,</span><span class="w">
</span><span class="nl">"rh"</span><span class="p">:</span><span class="w"> </span><span class="s2">"0.AXYAFoxqAF6E29830mEYB5Wx20IBWUEePwwXINRAoMUwcCJHG5KZAAA."</span><span class="p">,</span><span class="w">
</span><span class="nl">"roles"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="w">
</span><span class="s2">"Machine.Isolate"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Event.Write"</span><span class="p">,</span><span class="w">
</span><span class="s2">"SecurityConfiguration.ReadWrite.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"IntegrationConfiguration.ReadWrite"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Machine.Scan"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Url.Read.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Ip.Read.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Ti.ReadWrite"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Ti.Read.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"User.Read.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Machine.ReadWrite.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Ti.ReadWrite.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Machine.LiveResponse"</span><span class="p">,</span><span class="w">
</span><span class="s2">"SecurityRecommendation.Read.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Machine.RestrictExecution"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Machine.StopAndQuarantine"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Alert.Read.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Software.Read.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"SecurityConfiguration.Read.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"File.Read.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Machine.CollectForensics"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Machine.Offboard"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Vulnerability.Read.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Library.Manage"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Machine.Read.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Score.Read.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"RemediationTasks.Read.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"Alert.ReadWrite.All"</span><span class="p">,</span><span class="w">
</span><span class="s2">"AdvancedQuery.Read.All"</span><span class="w">
</span><span class="p">],</span><span class="w">
</span><span class="nl">"sub"</span><span class="p">:</span><span class="w"> </span><span class="s2">"22222222-2222-2222-2222-222222222222"</span><span class="p">,</span><span class="w">
</span><span class="nl">"tenant_region_scope"</span><span class="p">:</span><span class="w"> </span><span class="s2">"NA"</span><span class="p">,</span><span class="w">
</span><span class="nl">"tid"</span><span class="p">:</span><span class="w"> </span><span class="s2">"11111111-1111-1111-1111-111111111111"</span><span class="p">,</span><span class="w">
</span><span class="nl">"uti"</span><span class="p">:</span><span class="w"> </span><span class="s2">"0gf-Rhig10GmG2T1G7kyvAA"</span><span class="p">,</span><span class="w">
</span><span class="nl">"ver"</span><span class="p">:</span><span class="w"> </span><span class="s2">"1.0"</span><span class="w">
</span><span class="p">}</span><span class="w">
</span></code></pre></div></div>
<h2 id="using-the-token-to-run-advanced-threat-hunting-queries">Using the Token to Run Advanced Threat Hunting Queries</h2>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">query</span> <span class="o">=</span> <span class="s">"""DeviceProcessEvents | where InitiatingProcessFileName =~ </span><span class="se">\"</span><span class="s">powershell.exe</span><span class="se">\"</span><span class="s">
| project Timestamp, FileName, InitiatingProcessFileName
| order by Timestamp desc
| limit 2"""</span>
<span class="n">url</span> <span class="o">=</span> <span class="s">"https://api.securitycenter.windows.com/api/advancedqueries/run"</span>
<span class="n">headers</span> <span class="o">=</span> <span class="p">{</span>
<span class="s">'Content-Type'</span> <span class="p">:</span> <span class="s">'application/json'</span><span class="p">,</span>
<span class="s">'Accept'</span> <span class="p">:</span> <span class="s">'application/json'</span><span class="p">,</span>
<span class="s">'Authorization'</span> <span class="p">:</span> <span class="s">"Bearer "</span> <span class="o">+</span> <span class="n">result</span><span class="p">[</span><span class="s">"access_token"</span><span class="p">]</span>
<span class="p">}</span>
<span class="n">data</span> <span class="o">=</span> <span class="p">{</span> <span class="s">'Query'</span> <span class="p">:</span> <span class="n">query</span> <span class="p">}</span>
<span class="n">response</span> <span class="o">=</span> <span class="n">requests</span><span class="p">.</span><span class="n">post</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">json</span><span class="o">=</span><span class="n">data</span><span class="p">,</span> <span class="n">headers</span><span class="o">=</span><span class="n">headers</span><span class="p">,</span> <span class="n">verify</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<span class="n">jsonResponse</span> <span class="o">=</span> <span class="n">response</span><span class="p">.</span><span class="n">json</span><span class="p">()</span>
<span class="n">jsonResponse</span>
</code></pre></div></div>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>{'Stats': {'ExecutionTime': 0.0157135,
'resource_usage': {'cache': {'memory': {'hits': 50,
'misses': 0,
'total': 50},
'disk': {'hits': 0, 'misses': 0, 'total': 0}},
'cpu': {'user': '00:00:00.0625000',
'kernel': '00:00:00',
'total cpu': '00:00:00.0625000'},
'memory': {'peak_per_node': 3670944}},
'dataset_statistics': [{'table_row_count': 2, 'table_size': 94}]},
'Schema': [{'Name': 'Timestamp', 'Type': 'DateTime'},
{'Name': 'FileName', 'Type': 'String'},
{'Name': 'InitiatingProcessFileName', 'Type': 'String'}],
'Results': [{'Timestamp': '2022-03-07T21:34:30.1187436Z',
'FileName': 'net.exe',
'InitiatingProcessFileName': 'powershell.exe'},
{'Timestamp': '2022-03-07T21:34:29.380998Z',
'FileName': 'csc.exe',
'InitiatingProcessFileName': 'powershell.exe'}]}
</code></pre></div></div>
<h2 id="summary">Summary</h2>
<p>If you have gotten this far, congratulations! You have Multifactor connectivity with the Microsoft Defender for Endpoint API.</p>BotTricker2020-03-24T17:33:28+00:002020-03-24T17:33:28+00:00https://jon.glass/blog/BotTricker<p>When I spent some time getting to know TrickBot, I found it was helpful to decrypt the modules it injects manually in Python instead of spending the time to debug each one.
The following is a rudimentary script designed to find custom base64 character sets inside of raw data.
Overall steps:</p>
<h2 id="finding-b64-charsets">Finding b64 charsets:</h2>
<ul>
<li>Find potential base64 character sets by using Regex to look for all 64 character strings containing A-Za-z0-9+/</li>
<li>Take each match and sort the string to put the characters in order</li>
<li>Compare to a sorted list of standard b64 characters.</li>
<li>If there is a match, then we know the string has 1 of each character in the base64 character set, just in a different order.</li>
</ul>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="kn">import</span> <span class="nn">base64</span>
<span class="kn">import</span> <span class="nn">re</span>
<span class="n">std_base64chars</span> <span class="o">=</span> <span class="s">"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"</span>
<span class="k">def</span> <span class="nf">append_padding</span><span class="p">(</span><span class="n">val</span><span class="p">):</span>
<span class="n">mod</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">val</span><span class="p">)</span> <span class="o">%</span> <span class="mi">3</span>
<span class="k">while</span> <span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">val</span><span class="p">)</span> <span class="o">%</span> <span class="mi">4</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">val</span> <span class="o">+=</span> <span class="s">"="</span>
<span class="k">return</span> <span class="n">val</span>
<span class="k">def</span> <span class="nf">findcustomb64keys</span><span class="p">(</span><span class="n">filedata</span><span class="p">):</span>
<span class="n">base64keys</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">potentialbase64keys</span> <span class="o">=</span> <span class="n">re</span><span class="p">.</span><span class="n">findall</span><span class="p">(</span><span class="sa">b</span><span class="s">"[A-Za-z0-9+/]{64}"</span><span class="p">,</span><span class="n">filedata</span><span class="p">)</span>
<span class="n">sorteddict</span> <span class="o">=</span> <span class="s">''</span><span class="p">.</span><span class="n">join</span><span class="p">(</span><span class="nb">sorted</span><span class="p">(</span><span class="n">std_base64chars</span><span class="p">))</span>
<span class="k">for</span> <span class="n">keystr</span> <span class="ow">in</span> <span class="n">potentialbase64keys</span><span class="p">:</span>
<span class="n">attempt</span> <span class="o">=</span> <span class="n">keystr</span><span class="p">.</span><span class="n">decode</span><span class="p">(</span><span class="s">'utf-8'</span><span class="p">)</span>
<span class="n">sorted_attempt</span> <span class="o">=</span> <span class="s">''</span><span class="p">.</span><span class="n">join</span><span class="p">(</span><span class="nb">sorted</span><span class="p">(</span><span class="n">attempt</span><span class="p">))</span>
<span class="k">if</span> <span class="n">sorted_attempt</span> <span class="o">==</span> <span class="n">sorteddict</span><span class="p">:</span>
<span class="n">base64keys</span> <span class="o">+=</span> <span class="p">[</span><span class="n">attempt</span><span class="p">]</span>
<span class="k">return</span> <span class="n">base64keys</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s">'module2.bin'</span><span class="p">,</span><span class="s">'rb'</span><span class="p">)</span> <span class="k">as</span> <span class="n">inputfile</span><span class="p">:</span>
<span class="n">rawdata</span> <span class="o">=</span> <span class="n">inputfile</span><span class="p">.</span><span class="n">read</span><span class="p">()</span>
<span class="n">keys</span> <span class="o">=</span> <span class="n">findcustomb64keys</span><span class="p">(</span><span class="n">rawdata</span><span class="p">)</span>
<span class="n">keys</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">keys</span><span class="p">))</span>
<span class="k">print</span><span class="p">(</span><span class="s">"Base64 character sets found in Raw Data:</span><span class="se">\n</span><span class="s">"</span><span class="o">+</span><span class="s">"</span><span class="se">\n</span><span class="s">"</span><span class="p">.</span><span class="n">join</span><span class="p">(</span><span class="n">keys</span><span class="p">))</span>
</code></pre></div></div>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>Base64 character sets found in Raw Data:
yocxm6hkRzWB70tqQLnvfaujIpN3F8Aw1/KUPS5deVEMD2G9O+ZCg4TYbJHsrXli
HJIA/CB+FGKLNOP3RSlUVWXYZfbcdeaghi5kmn0pqrstuvwx89o12467MEDyzQjT
</code></pre></div></div>
<h2 id="decoding-potential-b64-strings">Decoding potential B64 strings</h2>
<ul>
<li>RegEx rawdata for any string that contains b64 chars and is between 5 and 4000 bytes in length</li>
<li>For each key found:
<ul>
<li>Translate the characters in the string from the custom character set to the regular set</li>
<li>Base64 decode as usual.</li>
<li>To cutdown the noise, I am checking to see if the decoded data contains any any string from 5 - 6000 chars long.
<ul>
<li>Not prefect</li>
</ul>
</li>
</ul>
</li>
</ul>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">potentialbase64strings</span> <span class="o">=</span> <span class="n">re</span><span class="p">.</span><span class="n">findall</span><span class="p">(</span><span class="sa">b</span><span class="s">"[A-Za-z0-9+/]{5,6000}"</span><span class="p">,</span><span class="n">rawdata</span><span class="p">)</span>
<span class="n">decodedstrings</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">keys</span><span class="p">:</span>
<span class="k">if</span> <span class="n">key</span> <span class="o">!=</span> <span class="s">"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"</span><span class="p">:</span>
<span class="k">for</span> <span class="n">encodedstring</span> <span class="ow">in</span> <span class="n">potentialbase64strings</span><span class="p">:</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">s</span> <span class="o">=</span> <span class="n">append_padding</span><span class="p">(</span><span class="n">encodedstring</span><span class="p">.</span><span class="n">decode</span><span class="p">(</span><span class="s">'utf-8'</span><span class="p">))</span>
<span class="n">translation</span> <span class="o">=</span> <span class="nb">str</span><span class="p">.</span><span class="n">maketrans</span><span class="p">(</span><span class="n">key</span><span class="p">,</span> <span class="n">std_base64chars</span><span class="p">)</span>
<span class="n">translatedstr</span> <span class="o">=</span> <span class="n">s</span><span class="p">.</span><span class="n">translate</span><span class="p">(</span><span class="n">translation</span><span class="p">)</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">base64</span><span class="p">.</span><span class="n">b64decode</span><span class="p">(</span><span class="n">translatedstr</span><span class="p">)</span>
<span class="c1">#lets just look for ascii strings
</span> <span class="n">justascii</span> <span class="o">=</span> <span class="n">re</span><span class="p">.</span><span class="n">search</span><span class="p">(</span><span class="sa">b</span><span class="s">"[</span><span class="se">\x00</span><span class="s">-</span><span class="se">\x7F</span><span class="s">]{5,6000}"</span><span class="p">,</span> <span class="n">data</span><span class="p">)</span>
<span class="k">if</span> <span class="n">justascii</span><span class="p">:</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">decodedstrings</span> <span class="o">+=</span> <span class="p">[</span><span class="n">justascii</span><span class="p">.</span><span class="n">group</span><span class="p">(</span><span class="mi">0</span><span class="p">).</span><span class="n">decode</span><span class="p">(</span><span class="s">'utf-8'</span><span class="p">)]</span>
<span class="k">except</span><span class="p">:</span>
<span class="n">decodedstrings</span> <span class="o">+=</span> <span class="p">[</span><span class="n">justascii</span><span class="p">.</span><span class="n">group</span><span class="p">(</span><span class="mi">0</span><span class="p">)]</span>
<span class="k">except</span><span class="p">:</span>
<span class="k">continue</span>
</code></pre></div></div>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="k">for</span> <span class="n">decoded</span> <span class="ow">in</span> <span class="n">decodedstrings</span><span class="p">[:</span><span class="mi">30</span><span class="p">]:</span>
<span class="k">print</span><span class="p">(</span><span class="n">decoded</span><span class="p">)</span>
</code></pre></div></div>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>AA
checkip.amazonaws.com
ipecho.net
ipinfo.io
api.ipify.org
icanhazip.com
myexternalip.com
wtfismyip.com
ip.anysrc.net
api.ipify.org
api.ip.sb
ident.me
www.myexternalip.com
/plain
/text
/?format=text
zen.spamhaus.org
cbl.abuseat.org
b.barracudacentral.org
dnsbl-1.uceprotect.net
spam.dnsbl.sorbs.net
CSName
Caption
CSDVersion
OSArchitecture
ProductType
BuildType
WindowsDirectory
SystemDirectory
BootDevice
</code></pre></div></div>
<h2 id="determining-which-module-is-which">Determining Which Module is Which</h2>
<p>This is an example of how to categorize the decoded strings based on observation.</p>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">signatures</span> <span class="o">=</span> <span class="p">{</span><span class="s">"[Main Bot]"</span><span class="p">:</span><span class="s">"<ipconf>"</span><span class="p">,</span>
<span class="s">"[UAC Bypass]"</span><span class="p">:</span><span class="s">"Software\Classes\AppX82a6gwre4fdg3bt635tn5ctqjf8msdd2"</span><span class="p">}</span>
<span class="k">for</span> <span class="n">sig</span> <span class="ow">in</span> <span class="n">signatures</span><span class="p">:</span>
<span class="k">if</span> <span class="n">signatures</span><span class="p">[</span><span class="n">sig</span><span class="p">]</span> <span class="ow">in</span> <span class="n">decodedstrings</span><span class="p">:</span>
<span class="k">print</span><span class="p">(</span><span class="s">"**** This appears to be"</span><span class="p">,</span> <span class="n">sig</span><span class="p">,</span> <span class="s">"****</span><span class="se">\n\n</span><span class="s">"</span><span class="p">)</span>
</code></pre></div></div>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>**** This appears to be [Main Bot] ****
</code></pre></div></div>
<p>That’s it. I hope you found this helpful.</p>Decoding AutoIT XOR Encryption Obfuscation2020-03-15T17:33:28+00:002020-03-15T17:33:28+00:00https://jon.glass/blog/AutoITXOR<p>Recently, I started looking at an AutoIt sample that contained some heavy obfuscation. After I ran the compiled binary through Exe2Aut, I was able to review the underlying script and I saw a lot of this stuff:</p>
<p><img src="data:image/png;base64,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" alt="Hello World" /></p>
<h3 id="starting-with-this-small-snippet-of-code">Starting with this small snippet of code:</h3>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>$poe($ergsduf(hsbduoekdcbl("327A3636344134413631343334413441303A303034403437353034473437344131313130
303030413032303035323536353030303041303230303734343B353035363537343334413633344134413444343130303041
3032303034363535344435303436303030413032303031323030304130323030343635353444353034363030304130323630
343B344734333530353B364134373447303A3036363B363737433737303B3032304030323630343B344734333530353B3641
34373447303A3036364436443732303B3041303230303436353534443530343630303041303230303132353A313131323132
313230303041303230303436353534443530343630303041303230303132353A313631323030303B37403030313230303746
", "2")))
</code></pre></div></div>
<h3 id="this-is-an-example-of-obfuscationencryption-used-in-autoit-malware">This is an example of obfuscation/encryption used in AutoIt malware.</h3>
<p>Starting from the inside out:</p>
<p>The <strong>“hsbduoekdcbl”</strong> function is used to XOR. The following is a hex string that is XORed with the pro<br />
vide key of “2”</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>327A3636344134413631343334413441303A3030344034373530344734373441313131303030304130323030353235363530
30303041303230303734343B3530353635373433344136333441344134443431303030413032303034363535344435303436
303030413032303031323030304130323030343635353444353034363030304130323630343B344734333530353B36413437
3447303A3036363B363737433737303B3032304030323630343B344734333530353B364134373447303A3036364436443732
303B3041303230303436353534443530343630303041303230303132353A3131313231323132303030413032303034363535
34443530343630303041303230303132353A313631323030303B37403030313230303746
</code></pre></div></div>
<h3 id="xoring-again-it-reveals-the-following-string">XORing again it reveals the following string:</h3>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>0x446C6C43616C6C28226B65726E656C3332222C2022707472222C20225669727475616C416C6C6F63222C202264776F7264
222C202230222C202264776F7264222C2042696E6172794C656E282449455A5529202B2042696E6172794C656E28244F4F50
292C202264776F7264222C2022307833303030222C202264776F7264222C20223078343022295B2230225D
</code></pre></div></div>
<p>The <strong>“ergsduf”</strong> function appears to be used to convert the hex string into text.</p>
<h3 id="this-is-of-course-another-hex-string-which-reveals">This is of course another hex string which reveals:</h3>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>DllCall("kernel32", "ptr", "VirtualAlloc", "dword", "0", "dword", BinaryLen($IEZU) + BinaryLen($OOP), "dword", "0x3000", "dword", "0x40")["0"]
</code></pre></div></div>
<p>The <strong>“poe”</strong> function seems like it just there to execute this deobfuscated code.</p>
<h3 id="lets-look-at-this-snippet-again-but-in-python-this-time">Lets look at this snippet again but in Python this time:</h3>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="kn">import</span> <span class="nn">re</span>
<span class="n">snippet</span> <span class="o">=</span> <span class="s">'$poe($ergsduf(hsbduoekdcbl("327A3636344134413631343334413441303A3030344034373530344734373441'</span>
<span class="n">snippet</span> <span class="o">+=</span> <span class="s">'31313130303030413032303035323536353030303041303230303734343B3530353635373433344136333441344134443431'</span>
<span class="n">snippet</span> <span class="o">+=</span> <span class="s">'3030304130323030343635353444353034363030304130323030313230303041303230303436353534443530343630303041'</span>
<span class="n">snippet</span> <span class="o">+=</span> <span class="s">'30323630343B344734333530353B364134373447303A3036363B363737433737303B3032304030323630343B344734333530'</span>
<span class="n">snippet</span> <span class="o">+=</span> <span class="s">'353B364134373447303A3036364436443732303B3041303230303436353534443530343630303041303230303132353A3131'</span>
<span class="n">snippet</span> <span class="o">+=</span> <span class="s">'31323132313230303041303230303436353534443530343630303041303230303132353A313631323030303B374030303132'</span>
<span class="n">snippet</span> <span class="o">+=</span> <span class="s">'30303746", "2")))'</span>
<span class="k">print</span><span class="p">(</span><span class="s">"We will use ([0-9A-F]+) to capture the Hex and (\d+) to capture the XOR key"</span><span class="p">)</span>
<span class="n">signature</span> <span class="o">=</span> <span class="s">'\$poe\(\$ergsduf\(hsbduoekdcbl\("([0-9A-F]+)", "(\d+)"\)\)\)'</span>
<span class="n">matches</span> <span class="o">=</span> <span class="n">re</span><span class="p">.</span><span class="n">findall</span><span class="p">(</span><span class="n">signature</span><span class="p">,</span><span class="n">snippet</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">matches</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="s">"</span><span class="se">\n</span><span class="s">"</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="s">"The first capture group collects the ciphertext:</span><span class="se">\n</span><span class="s">"</span><span class="p">,</span><span class="n">matches</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">])</span>
<span class="k">print</span><span class="p">(</span><span class="s">"The second collects the XOR key:"</span><span class="p">,</span><span class="n">matches</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">1</span><span class="p">])</span>
</code></pre></div></div>
<p>We will use ([0-9A-F]+) to capture the Hex and (\d+) to capture the XOR key:</p>
<p>’$poe($ergsduf(hsbduoekdcbl(”([0-9A-F]+)”, “(\d+)”)))’</p>
<p>This returns:</p>
<p><code class="language-plaintext highlighter-rouge">[('327A36363441344136...omitted', '2')]</code></p>
<p>The first capture group collects the ciphertext: 327A36363441344136…omitted
The second collects the XOR key: 2</p>
<h3 id="with-this-match-we-can-now-perform-the-operation-and-return-the-data-we-need">With this match we can now perform the operation and return the data we need…</h3>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="k">for</span> <span class="n">match</span> <span class="ow">in</span> <span class="n">matches</span><span class="p">:</span>
<span class="n">ciphertext</span> <span class="o">=</span> <span class="nb">bytearray</span><span class="p">.</span><span class="n">fromhex</span><span class="p">(</span><span class="n">match</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
<span class="n">key</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">match</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
<span class="n">firsthex</span> <span class="o">=</span> <span class="s">''</span>
<span class="k">for</span> <span class="n">character</span> <span class="ow">in</span> <span class="n">ciphertext</span><span class="p">:</span>
<span class="n">firsthex</span> <span class="o">+=</span> <span class="nb">chr</span><span class="p">(</span><span class="n">character</span> <span class="o">^</span> <span class="n">key</span><span class="p">)</span>
<span class="n">cleartext</span> <span class="o">=</span> <span class="n">firsthex</span><span class="p">[</span><span class="mi">2</span><span class="p">:]</span>
<span class="n">cleartext</span> <span class="o">=</span> <span class="nb">bytearray</span><span class="p">.</span><span class="n">fromhex</span><span class="p">(</span><span class="n">cleartext</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">cleartext</span><span class="p">.</span><span class="n">decode</span><span class="p">(</span><span class="s">'utf8'</span><span class="p">))</span>
</code></pre></div></div>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>DllCall("kernel32", "ptr", "VirtualAlloc", "dword", "0", "dword", BinaryLen($IEZU) + BinaryLen($OOP), "dword", "0x3000", "dword", "0x40")["0"]
</code></pre></div></div>
<h3 id="additionally-lets-use-regex-to-replace-the-original-text-so-we-can-ignore-the-obfuscation-altogether">Additionally, lets use RegEx to replace the original text so we can ignore the obfuscation altogether…</h3>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">decoded</span> <span class="o">=</span> <span class="n">re</span><span class="p">.</span><span class="n">sub</span><span class="p">(</span><span class="s">'\$poe\(\$ergsduf\(hsbduoekdcbl\("([0-9A-F]+)", "(\d+)"\)\)\)'</span><span class="p">,</span><span class="n">cleartext</span><span class="p">.</span><span class="n">decode</span><span class="p">(</span><span class="s">'utf8'</span><span class="p">),</span><span class="n">snippet</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">decoded</span><span class="p">)</span>
</code></pre></div></div>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>DllCall("kernel32", "ptr", "VirtualAlloc", "dword", "0", "dword", BinaryLen($IEZU) + BinaryLen($OOP), "dword", "0x3000", "dword", "0x40")["0"]
</code></pre></div></div>
<h3 id="lets-kick-this-up-a-notch-and-make-it-scale-to-cover-the-entire-file-instead-of-just-this-snippet">Lets kick this up a notch and make it scale to cover the entire file instead of just this snippet:</h3>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="kn">import</span> <span class="nn">re</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s">'autoit.txt'</span><span class="p">,</span> <span class="s">'r'</span><span class="p">)</span> <span class="k">as</span> <span class="n">autoitfile</span><span class="p">:</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">autoitfile</span><span class="p">.</span><span class="n">read</span><span class="p">()</span>
<span class="n">newdata</span> <span class="o">=</span> <span class="s">''</span>
<span class="c1">#loop through each line of the script
</span><span class="k">for</span> <span class="n">line</span> <span class="ow">in</span> <span class="n">data</span><span class="p">.</span><span class="n">split</span><span class="p">(</span><span class="s">'</span><span class="se">\n</span><span class="s">'</span><span class="p">):</span>
<span class="n">signature</span> <span class="o">=</span> <span class="s">'\$poe\(\$ergsduf\(hsbduoekdcbl\("([0-9A-F]+)", "(\d+)"\)\)\)'</span>
<span class="n">regexmatches</span> <span class="o">=</span> <span class="n">re</span><span class="p">.</span><span class="n">findall</span><span class="p">(</span><span class="n">signature</span><span class="p">,</span><span class="n">line</span><span class="p">)</span>
<span class="k">if</span> <span class="n">regexmatches</span><span class="p">:</span>
<span class="k">for</span> <span class="n">match</span> <span class="ow">in</span> <span class="n">regexmatches</span><span class="p">:</span>
<span class="n">ciphertext</span> <span class="o">=</span> <span class="nb">bytearray</span><span class="p">.</span><span class="n">fromhex</span><span class="p">(</span><span class="n">match</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
<span class="n">key</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">match</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
<span class="n">firsthex</span> <span class="o">=</span> <span class="s">''</span>
<span class="k">for</span> <span class="n">character</span> <span class="ow">in</span> <span class="n">ciphertext</span><span class="p">:</span>
<span class="n">firsthex</span> <span class="o">+=</span> <span class="nb">chr</span><span class="p">(</span><span class="n">character</span> <span class="o">^</span> <span class="n">key</span><span class="p">)</span>
<span class="n">cleartext</span> <span class="o">=</span> <span class="n">firsthex</span><span class="p">[</span><span class="mi">2</span><span class="p">:]</span>
<span class="n">cleartext</span> <span class="o">=</span> <span class="nb">bytearray</span><span class="p">.</span><span class="n">fromhex</span><span class="p">(</span><span class="n">cleartext</span><span class="p">).</span><span class="n">decode</span><span class="p">(</span><span class="s">'utf8'</span><span class="p">)</span>
<span class="c1">#replace original broke, with shiny new woke
</span> <span class="n">line</span> <span class="o">=</span> <span class="n">re</span><span class="p">.</span><span class="n">sub</span><span class="p">(</span><span class="n">signature</span><span class="p">,</span><span class="n">re</span><span class="p">.</span><span class="n">escape</span><span class="p">(</span><span class="n">cleartext</span><span class="p">),</span> <span class="n">line</span><span class="p">)</span>
<span class="n">newdata</span> <span class="o">+=</span> <span class="s">''</span><span class="p">.</span><span class="n">join</span><span class="p">([</span><span class="n">line</span><span class="p">,</span><span class="s">'</span><span class="se">\n</span><span class="s">'</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">newdata</span> <span class="o">+=</span> <span class="s">''</span><span class="p">.</span><span class="n">join</span><span class="p">([</span><span class="n">line</span><span class="p">,</span><span class="s">'</span><span class="se">\n</span><span class="s">'</span><span class="p">])</span>
<span class="k">print</span><span class="p">(</span><span class="s">'Decoded'</span><span class="p">,</span><span class="n">numofmatches</span><span class="p">,</span> <span class="s">'lines'</span><span class="p">)</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s">'newautoit.txt'</span><span class="p">,</span><span class="s">'w'</span><span class="p">)</span> <span class="k">as</span> <span class="n">newautoitfile</span><span class="p">:</span>
<span class="n">newautoitfile</span><span class="p">.</span><span class="n">write</span><span class="p">(</span><span class="n">newdata</span><span class="p">)</span>
</code></pre></div></div>
<p><strong>Decoded 11 lines</strong></p>
<p>What did this do? Well line 462 of this script in the original autoit.txt file reads like this:</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>$poe($ergsduf(hsbduoekdcbl("31793535374237423432363536333634373236353432373436353535373036353730
33393335353434343434353433423331323033423331333535383534344034343338", "1")))
</code></pre></div></div>
<p>in the new file we have replaced it’s actual code:</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>DllStructSetData($EUUE, 1, $IEZU)
</code></pre></div></div>
<p>Our signature is fairly specifc to a certain combination of functions: <strong>poe</strong>, <strong>ergsduf</strong>, and <strong>hsbduoekdcbl</strong> BUT there are others in this mess that do the same thing.</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>If $qnqhwwqbvarvaoqrrvcrunt = 6957 Then
$poe($e(fcoupewxiogl("31793535374237423532373037423742333933333743373436333744373437423232323333
4437353742374233333342333133333733374737473742373437303744333333423331333334363747363632373235353437
4437303733374237343436374736363237323535373632343337343735373836333734373236353738374737443333334233
31333337333747374737423734373037443333334233313333323133333338", "1")))
Else
Local $mxboopmlxnjz = $poe($v1(fcoupewxiogl("307832343637364436453734364532303236323032323435343
6343634363436333634333330333034333337333833353436333434363435343634363436343633353433333434323336343
5333634363433333733383335343633383436343534363436343634363337333733363435333433343336343334333337333
8333534363433343634353436343634363436333634333337333333353433333434363433333733383335333033303436343
6343634363436343633363433333633353333333333333332343333373338333533303334343634363436343634363436333
2343533363334333634333336343333383338333833353330333834363436343634363436343634333337333433353435333
0333733353337333333363335333733323433333733343335343533343333333333333332333234353336333433363336343
3333733343335343533383336343333363433333833383334333534353431343333373338333533303433343634363436343
6343634363334343533373334333434363337333034333337333833353232", "0")))
</code></pre></div></div>
<p>From performing the same steps we can see that poe, e, fcoupewxiogl performs the same way so lets update our signature to capture others:</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>signature = '\$poe\(\$(v1|e|gfbvo|rfo|fooi4e|ergsduf|erzgf|ayudergfv|sdvfi|zeyc|grfeus|ufd)'
signature += '\((fcoupewxiogl|hsbduoekdcbl)\("([0-9A-F]+)", "(\d+)"\)\)\)'
</code></pre></div></div>
<p>Here is an updated script with all of the redundant variables that perform the same actions on the encrypted strings:</p>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="kn">import</span> <span class="nn">re</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s">'autoit.txt'</span><span class="p">,</span> <span class="s">'r'</span><span class="p">)</span> <span class="k">as</span> <span class="n">autoitfile</span><span class="p">:</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">autoitfile</span><span class="p">.</span><span class="n">read</span><span class="p">()</span>
<span class="n">numofmatches</span> <span class="o">=</span> <span class="mi">0</span>
<span class="n">newdata</span> <span class="o">=</span> <span class="s">''</span>
<span class="k">for</span> <span class="n">line</span> <span class="ow">in</span> <span class="n">data</span><span class="p">.</span><span class="n">split</span><span class="p">(</span><span class="s">'</span><span class="se">\n</span><span class="s">'</span><span class="p">):</span>
<span class="n">signature</span> <span class="o">=</span> <span class="s">'\$poe\(\$(v1|e|gfbvo|rfo|fooi4e|ergsduf|erzgf|ayudergfv|sdvfi|zeyc|grfeus|ufd)\((fcoupewxiogl|hsbduoekdcbl)\("([0-9A-F]+)", "(\d+)"\)\)\)'</span>
<span class="n">regexmatches</span> <span class="o">=</span> <span class="n">re</span><span class="p">.</span><span class="n">findall</span><span class="p">(</span><span class="n">signature</span><span class="p">,</span><span class="n">line</span><span class="p">)</span>
<span class="k">if</span> <span class="n">regexmatches</span><span class="p">:</span>
<span class="n">numofmatches</span> <span class="o">+=</span> <span class="mi">1</span>
<span class="k">for</span> <span class="n">match</span> <span class="ow">in</span> <span class="n">regexmatches</span><span class="p">:</span>
<span class="c1">#we'll need to adjust the arrays we are calling because we are capture more fields
</span> <span class="c1">#('e', 'fcoupewxiogl', '347C31343336324232373231333733373037333133303242303D33303134303D3030363D', '4')
</span> <span class="n">ciphertext</span> <span class="o">=</span> <span class="nb">bytearray</span><span class="p">.</span><span class="n">fromhex</span><span class="p">(</span><span class="n">match</span><span class="p">[</span><span class="mi">2</span><span class="p">])</span>
<span class="n">key</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">match</span><span class="p">[</span><span class="mi">3</span><span class="p">])</span>
<span class="n">firsthex</span> <span class="o">=</span> <span class="s">''</span>
<span class="k">for</span> <span class="n">character</span> <span class="ow">in</span> <span class="n">ciphertext</span><span class="p">:</span>
<span class="n">firsthex</span> <span class="o">+=</span> <span class="nb">chr</span><span class="p">(</span><span class="n">character</span> <span class="o">^</span> <span class="n">key</span><span class="p">)</span>
<span class="n">cleartext</span> <span class="o">=</span> <span class="n">firsthex</span><span class="p">[</span><span class="mi">2</span><span class="p">:]</span>
<span class="n">cleartext</span> <span class="o">=</span> <span class="nb">bytearray</span><span class="p">.</span><span class="n">fromhex</span><span class="p">(</span><span class="n">cleartext</span><span class="p">).</span><span class="n">decode</span><span class="p">(</span><span class="s">'utf8'</span><span class="p">)</span>
<span class="c1">#replace original broke, with shiny new woke
</span> <span class="n">line</span> <span class="o">=</span> <span class="n">re</span><span class="p">.</span><span class="n">sub</span><span class="p">(</span><span class="n">signature</span><span class="p">,</span><span class="n">re</span><span class="p">.</span><span class="n">escape</span><span class="p">(</span><span class="n">cleartext</span><span class="p">),</span> <span class="n">line</span><span class="p">)</span>
<span class="n">newdata</span> <span class="o">+=</span> <span class="s">''</span><span class="p">.</span><span class="n">join</span><span class="p">([</span><span class="n">line</span><span class="p">,</span><span class="s">'</span><span class="se">\n</span><span class="s">'</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">newdata</span> <span class="o">+=</span> <span class="s">''</span><span class="p">.</span><span class="n">join</span><span class="p">([</span><span class="n">line</span><span class="p">,</span><span class="s">'</span><span class="se">\n</span><span class="s">'</span><span class="p">])</span>
<span class="k">print</span><span class="p">(</span><span class="s">'Decoded'</span><span class="p">,</span><span class="n">numofmatches</span><span class="p">,</span> <span class="s">'lines'</span><span class="p">)</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s">'newautoit.txt'</span><span class="p">,</span><span class="s">'w'</span><span class="p">)</span> <span class="k">as</span> <span class="n">newautoitfile</span><span class="p">:</span>
<span class="n">newautoitfile</span><span class="p">.</span><span class="n">write</span><span class="p">(</span><span class="n">newdata</span><span class="p">)</span>
</code></pre></div></div>
<p><strong>Decoded 303 lines</strong></p>
<p>BAM! 303 lines of deobfuscated code!</p>
<p>Are we done? Nah! How is more obfuscated stuff?!</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>If $yufanpeqeyqcweddlyi == 8.37539918579835 Then
Dim $payloadexist = $poe($erzgf(fcoupewxiogl("3078343636393643363534353738363937333734373332383234373036313739364336463631363435303631373436383239", fcoupewxiogl("32", "2"))))
Else
</code></pre></div></div>
<p>Some of these do not decrypt because they break our RegEx pattern.<br />
UGH! What to do? Well if we look at them… the can theoretically be ignored. Why? This is an XOR routine that XORing the Hex value 32 with it’s ascii counterpart “2”. <br />
Since when we XOR anything with itself, we will get 0 for these. So this equates to:</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>$poe($erzgf(fcoupewxiogl("3078343636393643363534353738363937333734373332383234373036313739364336463631363435303631373436383239", "0" )))
</code></pre></div></div>
<p>Taking it a step further, since XORing something by 0 doesn’t change the value, this technically doesn’t change our data but since it dorks with our pattern, we will account for it. Here we are going to use a <strong>while loop</strong> to regex, decode, rinse, repeat cycle until the nested decryption goes away.</p>
<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="kn">import</span> <span class="nn">re</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s">'autoit.txt'</span><span class="p">,</span> <span class="s">'r'</span><span class="p">)</span> <span class="k">as</span> <span class="n">autoitfile</span><span class="p">:</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">autoitfile</span><span class="p">.</span><span class="n">read</span><span class="p">()</span>
<span class="n">numofmatches</span> <span class="o">=</span> <span class="mi">0</span>
<span class="n">newdata</span> <span class="o">=</span> <span class="s">''</span>
<span class="n">signature</span> <span class="o">=</span> <span class="s">'\$poe\(\$(v1|e|gfbvo|rfo|fooi4e|ergsduf|erzgf|ayudergfv|sdvfi|zeyc|grfeus|ufd)\((fcoupewxiogl|hsbduoekdcbl)\("([0-9A-F]+)", "(\d+)"\)\)\)'</span>
<span class="n">nestedsignature</span> <span class="o">=</span> <span class="s">'(fcoupewxiogl|hsbduoekdcbl)\("([0-9A-F]+)", "(\d+)"\)'</span>
<span class="k">for</span> <span class="n">line</span> <span class="ow">in</span> <span class="n">data</span><span class="p">.</span><span class="n">split</span><span class="p">(</span><span class="s">'</span><span class="se">\n</span><span class="s">'</span><span class="p">):</span>
<span class="n">regexmatches</span> <span class="o">=</span> <span class="n">re</span><span class="p">.</span><span class="n">findall</span><span class="p">(</span><span class="n">signature</span><span class="p">,</span><span class="n">line</span><span class="p">)</span>
<span class="n">nestedmatches</span> <span class="o">=</span> <span class="n">re</span><span class="p">.</span><span class="n">findall</span><span class="p">(</span><span class="n">nestedsignature</span><span class="p">,</span><span class="n">line</span><span class="p">)</span>
<span class="k">if</span> <span class="n">regexmatches</span><span class="p">:</span>
<span class="n">numofmatches</span> <span class="o">+=</span> <span class="mi">1</span>
<span class="k">for</span> <span class="n">match</span> <span class="ow">in</span> <span class="n">regexmatches</span><span class="p">:</span>
<span class="c1">#we'll need to adjust the arrays we are calling because we are capture more fields
</span> <span class="c1">#('e', 'fcoupewxiogl', '347C31343336324232373231333733373037333133303242303D33303134303D3030363D', '4')
</span> <span class="n">ciphertext</span> <span class="o">=</span> <span class="nb">bytearray</span><span class="p">.</span><span class="n">fromhex</span><span class="p">(</span><span class="n">match</span><span class="p">[</span><span class="mi">2</span><span class="p">])</span>
<span class="n">key</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">match</span><span class="p">[</span><span class="mi">3</span><span class="p">])</span>
<span class="n">firsthex</span> <span class="o">=</span> <span class="s">''</span>
<span class="k">for</span> <span class="n">character</span> <span class="ow">in</span> <span class="n">ciphertext</span><span class="p">:</span>
<span class="n">firsthex</span> <span class="o">+=</span> <span class="nb">chr</span><span class="p">(</span><span class="n">character</span> <span class="o">^</span> <span class="n">key</span><span class="p">)</span>
<span class="n">cleartext</span> <span class="o">=</span> <span class="n">firsthex</span><span class="p">[</span><span class="mi">2</span><span class="p">:]</span>
<span class="n">cleartext</span> <span class="o">=</span> <span class="nb">bytearray</span><span class="p">.</span><span class="n">fromhex</span><span class="p">(</span><span class="n">cleartext</span><span class="p">).</span><span class="n">decode</span><span class="p">(</span><span class="s">'utf8'</span><span class="p">)</span>
<span class="c1">#replace original broke, with shiny new woke
</span> <span class="n">line</span> <span class="o">=</span> <span class="n">re</span><span class="p">.</span><span class="n">sub</span><span class="p">(</span><span class="n">signature</span><span class="p">,</span><span class="n">re</span><span class="p">.</span><span class="n">escape</span><span class="p">(</span><span class="n">cleartext</span><span class="p">),</span> <span class="n">line</span><span class="p">)</span>
<span class="c1">#print(cleartext)
</span> <span class="n">newdata</span> <span class="o">+=</span> <span class="s">''</span><span class="p">.</span><span class="n">join</span><span class="p">([</span><span class="n">line</span><span class="p">,</span><span class="s">'</span><span class="se">\n</span><span class="s">'</span><span class="p">])</span>
<span class="k">elif</span> <span class="n">nestedmatches</span><span class="p">:</span>
<span class="k">while</span> <span class="n">nestedmatches</span><span class="p">:</span>
<span class="n">numofmatches</span> <span class="o">+=</span> <span class="mi">1</span>
<span class="n">ciphertext</span> <span class="o">=</span> <span class="nb">bytearray</span><span class="p">.</span><span class="n">fromhex</span><span class="p">(</span><span class="n">nestedmatches</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">1</span><span class="p">])</span>
<span class="n">key</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">nestedmatches</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">2</span><span class="p">])</span>
<span class="n">firsthex</span> <span class="o">=</span> <span class="s">''</span>
<span class="k">for</span> <span class="n">character</span> <span class="ow">in</span> <span class="n">ciphertext</span><span class="p">:</span>
<span class="n">firsthex</span> <span class="o">+=</span> <span class="nb">chr</span><span class="p">(</span><span class="n">character</span> <span class="o">^</span> <span class="n">key</span><span class="p">)</span>
<span class="k">if</span> <span class="n">firsthex</span><span class="p">[:</span><span class="mi">2</span><span class="p">]</span> <span class="o">==</span> <span class="s">"0x"</span><span class="p">:</span>
<span class="n">cleartext</span> <span class="o">=</span> <span class="n">firsthex</span><span class="p">[</span><span class="mi">2</span><span class="p">:]</span>
<span class="c1">#Lets try to decode the message to utf8
</span> <span class="k">try</span><span class="p">:</span>
<span class="n">cleartext</span> <span class="o">=</span> <span class="nb">bytearray</span><span class="p">.</span><span class="n">fromhex</span><span class="p">(</span><span class="n">cleartext</span><span class="p">).</span><span class="n">decode</span><span class="p">(</span><span class="s">'utf8'</span><span class="p">)</span>
<span class="k">except</span><span class="p">:</span>
<span class="c1">#if it doesn't work because it in binary data, ignore and just give me the hex.
</span> <span class="n">cleartext</span> <span class="o">=</span> <span class="n">firsthex</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">cleartext</span> <span class="o">=</span> <span class="n">firsthex</span>
<span class="n">line</span> <span class="o">=</span> <span class="n">re</span><span class="p">.</span><span class="n">sub</span><span class="p">(</span><span class="n">nestedsignature</span><span class="p">,</span><span class="s">'"'</span><span class="o">+</span><span class="n">re</span><span class="p">.</span><span class="n">escape</span><span class="p">(</span><span class="n">cleartext</span><span class="p">)</span><span class="o">+</span><span class="s">'"'</span><span class="p">,</span> <span class="n">line</span><span class="p">)</span>
<span class="n">nestedmatches</span> <span class="o">=</span> <span class="n">re</span><span class="p">.</span><span class="n">findall</span><span class="p">(</span><span class="n">nestedsignature</span><span class="p">,</span><span class="n">line</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">newdata</span> <span class="o">+=</span> <span class="s">''</span><span class="p">.</span><span class="n">join</span><span class="p">([</span><span class="n">line</span><span class="p">,</span><span class="s">'</span><span class="se">\n</span><span class="s">'</span><span class="p">])</span>
<span class="k">print</span><span class="p">(</span><span class="s">'Decoded'</span><span class="p">,</span><span class="n">numofmatches</span><span class="p">,</span> <span class="s">'lines'</span><span class="p">)</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s">'newautoit.txt'</span><span class="p">,</span><span class="s">'w'</span><span class="p">)</span> <span class="k">as</span> <span class="n">newautoitfile</span><span class="p">:</span>
<span class="n">newautoitfile</span><span class="p">.</span><span class="n">write</span><span class="p">(</span><span class="n">newdata</span><span class="p">)</span>
</code></pre></div></div>
<p><strong>Decoded 390 lines</strong></p>
<p>There we go! 390 lines we didn’t need to decode by hand.<br />
Plus with minor tweaks, hopefully this could be used for the next sample and maximize my ROI.</p>
<p>While I will be the first to admit, this decryption could perhaps be tackled in a more efficient manner by ignoring all of the names of the functions, I wanted to make the output as clean as possible for readability and highlight the techniques you can use to solve these sort of problems in the future.</p>
<p>Well, that is it. thanks for reading!</p>Cybersecurity Zero to Hero with CyberChef2019-06-23T20:33:28+00:002019-06-23T20:33:28+00:00https://jon.glass/blog/CyberChef-Slides-From-RVASec<p>Here are the slides from my RVASec this year.</p>
<p><a href="/assets/files/CyberChef.pptx">Cybersecurity Zero to Hero with CyberChef</a></p>Analysis of Fiesta EK2018-12-26T20:33:28+00:002018-12-26T20:33:28+00:00https://jon.glass/blog/Fiesta-Analysis<p>For funsies, snagged a Traffic Analysis Exercise from Malware-Traffic-Analysis.net. If you want to follow along at home, here is the link:
<a href="http://www.malware-traffic-analysis.net/2014/12/08/index.html">http://www.malware-traffic-analysis.net/2014/12/08/index.html</a></p>
<p>A review of the network packet capture (PCAP) revealed that 192.168.204.137 was the source or destination for all of the network traffic. NetBIOS queries identify this host as “38NTRGDFQKR-PC”.
<img src="/images/fiestaEKnbns.png" alt="Hostname" /></p>
<p>Network artifacts within this PCAP are consistent with 5 stages of the Fiesta Exploit Kit:</p>
<p><img src="/images/fiestaEKchain.png" alt="Fiesta EK Stages" /></p>
<h3 id="stage-1-visiting-compromised-site"><strong>Stage 1: Visiting Compromised Site</strong></h3>
<p>Artifacts reflect the incident resulted from a user clicking a Google.de link that redirect the user to ExcelForum.com. ExcelForum, a Microsoft Excel user forum was running vBulletin 4.1.8 at the time of the attack and was vulnerable to several CVEs including CVE-2012-4328.</p>
<h3 id="stage-2-gate-redirection"><strong>Stage 2: Gate Redirection</strong></h3>
<p><img src="/images/fiestaEKtcp2.png" alt="TCP Stream 2" /></p>
<p>In tcp.stream 2, analysis reveals the malicious JavaScript injected under the the script reference for the CKEditor in the HEAD section of the page. The JavaScript references a external site: hxxp://magggnitia.com/?Q2WP=p4VpeSdhe5ba&nw3=9n6MZfU9I_1Ydl8y&9M5to=_8w6t8o4W_abrev&GgiMa=8Hfr8Tlcgkd0sfV&t6Mry=I6n2. In WireShark, we can see this being delivered in tcp.stream 8. After extracting the payload, I chucked it into CyberChef to take a look at it.
<a href="https://gchq.github.io/CyberChef/#recipe=From_Hex('Auto')Gunzip()JavaScript_Beautify('%5C%5Ct','Auto',true,true)Find_/_Replace(%7B'option':'Regex','string':'%5C%5C%5C'%20%5C%5C%2B%20%5C%5C%5C''%7D,'',true,false,true,false)&input=MWY4YjA4MDAwMDAwMDAwMDAwMDM3NTU1NTk1M2RiM2ExNGZlMmI4NjA3NjQ0ZjA0YjE0MzkzMTQzNGJhNzc0YTA5ZDA4NWFkMGQyZDI1ZTMwN2Q5OTY2ZDA1NDdkZWU0MmM0ZGYzZGY3YmJjMjQwZTc3ZTYzZTQ5M2EzYWU3ZmJjZTJhNGQ0NTkwNjcxNDQ5MzYxNzAxNTM3MTg2ODgxYmM3ZjI5NDIyMmY3NjhiMTk5NzBhMTEyNTIyNTVkMDg1OTA1ZWJjMjA0OTE2N2JlZjY5MjU5YTU0OWEzNjUxNWNlNjQxMjM5YTk2NzAzNjk5YjM0YzViNDg2ZjZiMTRkYzNkY2Q1NDM2NzY0NzU3MTQ4NTRhMjVlN2E4ODNiYTVkNGYwNGIwOGEwNTc3MjRhYzZjYzY0ZjA0YWNiMjNiNzg1NWIwMjZhMmJmOGM0YmJkODdmOGU2MjdhYzVmYWY1ZjE2MTlhY2QzNjc3ZTdkMDllYmY1ZTljM2YxMjc1OGZiYTg2MjAzNzcyOTMwOWU2Y2RkMjYzNzhiNmNiNWNjMWY1ZjJlNjljYjRlZmM0MmJhNGFjNDUyY2JiOWZhMThjN2FmODJlYjEyODhmMTljNDUwNWM3N2M5OTg4OGNlN2M2MWE0MDRlZGNlYTlhOTZkNzFkNDQ1MTg3ZTcyZTRiYjg1ZTY5MWE5ZDQzYTIzNWRhZjRiMGQzZWM0ZTU0N2M3ZDNiZmVhZTMyMjEwM2JkNTI0OTk4MGE2OWY3OTA2NDVjMTU5OTI0OWIxZDdkZjA4NmRlNTg5NzExMzQ4NDQ4NDM5ZDk2YmY4YTJkZTcyYzczYzNlYTY2ZWI0ZTIzNTdjMDQ2NjUxMTQ1ZDUzOWY2N2QxMDY5NTQzM2FiMjM5NzVlYjUxN2JlYTZkNzY4MjcxMTk3ODEwYWI1N2YzNGQzZDBkNjNiZjVlNjEyNmFjNTk3ZjdiZTVlZDMxOTk1NWRhMzczNDBiNTYzYWIzNWU5ZDBjNmE3MDY5MGQ0NTRmZmMxNDEwNGUxYzZhNzFhYWNkMjZhOTBkZTU4MzQyODliM2EyMDkwOTc5NTJjNjQ5M2YyNDYyOTJmOWNiY2NlNmQ4ZDg5Y2IwMDBkODM2YzM2NzU3YTliNzRlYzY1NzkxYzNlM2Q1ZmFiMWY5ZjNlYTc0MjM3ZDZjMmQ3MGZkYWJjMWZiYWIzNmZkM2JiNTFmMTNkZjE2ZmQzZmI0M2EzYWVjMWI2YTY5MjJmYjQ0YmE2Yjg2ZTkwNmQ3MTAxN2QyYzY2NWNkZjllODNlNjZjNzRjYzY1YmYzN2U4YmJhNjY5OTBmY2ZmZjAzMTFhZjYzYzY2Nzk4ZTM1MThiYTE2MWIzODY3ODNlMWMwN2JlNzlkYmQzNzA3Y2NlMmJlNjlhMjVkZmIzNWVkYTJhOWFjZTAxYjFlZTU3Y2RkMDg3YzA2ODc0ZDFiZGZmNGY5Y2JhOGI4N2JiZGZjZmQ0MTlmMGViMzNhODJjNTE5ZjZmYjIxNjY3MzFjNTkyNGIyMjg4YTY1MTQzMzBmMTEzNmE3ODg3OWRlNjgwZWMzZjE1NWU0MzBiNDFjODYxZDc0NDFhYzE0NzNjM2VhMDY5MWM1MTk0NTk3ZjdiNzFmNjNhOTRhNGRiMGU1NjA1ZDhkZmQ4NGNkZWQ3Zjc3M2IxZGE4NGFkYWYzN2FjODI3MDA2NWViOTE1NWM5NWExZmQ1OGZmOWEzZjA5Y2ZiMmJiZGY2MmY1ZDkxNzQ0NTUxOTFmM2VjNDM1MDExNmVhMzJkNWY5MTQ5YmFiMmY3YTYyNGJlN2M4YzllYzJkYjg3NDI1Zjk5MTE5Njg5NTU2MzI0NDM5MjBjMjk1MjNjNmZjZDQxNjE5MjBjNmRiZDU0NmExMWFlMTJmN2Y5NjY3YWY3YzU3ZjY5ZThmZDk0ZjgyOWRkNzM2YTZiYmZjN2Q1ZmQyOWU0ZTAxZGU5MGFlY2E3YzY5ZjNmZmIzN2NiOWRiY2U1Nzg3ZTQ4YzVhZjBiNDdjZTFiMGEyNmIwYzM4OWMzYTlkZTFkNjdjMjgzMThiYmMyMjA0Y2JjNjFhZDlhYjEwNTc2Mzg2NjAyN2FiMDcxYzY3YzUzZjZhYTBmNWFiZWQ5ZDVhZjZmOWYyZjMyOTVjYTg2NzA5YTBlNzA2MTE2MzhlYWUxNTBlMjZjZThlMjU0MGRmMWNhYzI3MjM2YzczZWMzY2UxY2IzMDBiYjg1YzRiZjhiM2U0ZTUyNzAwZTdhMjE4OWYzZjJiOTJkMjFjZjE5NmM5YzNjOGU4YWYyZTFlNTI0ZTJiZTNhM2ZiNmZhNzBlODlkMjY0YjUyNGFlM2E0OTQ5Y2MyNmU5ODJjMTEwMTY4OGFmMmNjNDU2NDA1M2QyNmZjYWM3ZWMxMTEwMTQ3Mjg3MmYzN2M1YzIyMmRhMTNlNTE4ZjIyOTg5NTUxNTQwYWFhMGZhNTgzZjI4YmQ1OTgwNTc3NWIxYjcwOGQyMmE3N2NlY2JkMTUyMmUwM2M0NTBiZTFhOTEwZGE5M2MxODdjMTQ1MTAwMjEwMzgwZWFkOWEyNDMwZjUxZjQzMTE0MTUzODY2MGU2NjYxY2U2NzQxNGQ1ZDAwNGEyMDdiZmQ0MmEwMjU4MTY1MDY0OTlhOGNjZjU5Yjk3ZTBlODY4YWY2NDQ3NDcwN2ZiNGQ2MmFjMjE5Yjk0MDUwNDUyNDVlYjU2MGZhNWFkYWYyY2EzOTQ0Y2MwMzc5YjgyNDY3NWYwNTliYjA3NWU3YjAyYjFkYmQ0OTk1NzAyNDg5MDRkNzc3ZjUwMzMzZjUxY2ZkNjIxNTg2MzYyZGExMzA4YzdkNjQxZDNkODZjZjZlNmI4MmRhZTQxZmUwMjg5YTRmN2JhOWIwNzAwMDA">(<img src="/images/fiestaEKgate.png" alt="Click to Open In CyberChef" /></a>
Using CyberChef we can see the script from magggnitia.com has the following notable functionalities:</p>
<ul>
<li>Compressed data</li>
<li>Light obfuscation</li>
<li>Uses DOMContentLoaded event listener to begin execution when the initial HTML document has been completely loaded and parsed</li>
<li>Checks for the following conditions before redirection
<ul>
<li>ThUXGtVIJqi() - Checks for the existence of the cmRjNEuSpfMqO cookie to prevent redundant infection. If the cookie does not exist, it will set it as a flag.</li>
<li>XPqiYBbnv() - Checks for the Existence of Trident in the UA string meaning the next stage payloads depend on attacking Internet Explorer.</li>
<li>Reviews User Agent String for Browser and OS Version attempting to exclude 64-bit processes. This is most likely because the next stage only contains 32-bit payloads.</li>
</ul>
</li>
<li>Redirects to hxxp://digiwebname.in/6ktpi5xo/PoHWLGZwrjXeGDG3P-I5 payload</li>
</ul>
<h3 id="stage-3-fiesta-ek-landing-page"><strong>Stage 3: Fiesta EK Landing Page</strong></h3>
<p>Starting with tcp.stream 29, we can see the Fiesta EK landing page from digiwebname.in has a large amount of moderately obfuscated JavaScript and presents a page with seemingly random words.
<img src="/images/fiestaEKlandingpage.png" alt="Landing Page" /> Most of the variables are encrypted and use the “boomp” function to decrypt. For me, it was easier to rewrite this in Python and use RegEx to deobfuscate the code at scale.
<img src="/images/fiestaEKpython.png" alt="Python" /></p>
<p>The following analysis is based on reverse engineering of the major functions within the landing page JavaScript:</p>
<ul>
<li><strong>lege5b()</strong>
<ul>
<li>Purpose: Deliver Shockwave Flash Exploit for Flash Player v11.2 from hxxp://digiwebname.in/6ktpi5xo/228759d200ad45b60a060c0c0702550b00010b0c015b540907060001060b560b</li>
<li>Applicable to 38NTRGDFQKR-PC: <strong>No.</strong></li>
<li>This was not available in the packet capture.</li>
</ul>
</li>
<li><strong>swapy5()</strong>
<ul>
<li>Purpose: Deliver Shockwave Flash Exploit for Flash Player v10.3 - 11.1 from hxxp://digiwebname.in/6ktpi5xo/69266c7425df8059030f0b0d0458060d040a010d0201070f030d0a000551050</li>
<li>Applicable to 38NTRGDFQKR-PC: <strong>No.</strong></li>
<li>This was not available in the packet capture.</li>
</ul>
</li>
<li><strong>naveo()</strong>
<ul>
<li>Purpose: Deliver Shockwave Flash Exploit for Flash Player 10.2 from hxxp://digiwebname.in/6ktpi5xo/3830948c194842760701040b0b0f095a010b000b0d560858060c0b060a060a5a</li>
<li>Applicable to 38NTRGDFQKR-PC: <strong>Yes.</strong> At the time of the incident, the network artifacts reflect the workstation was running Flash Player 10.2 and this exploit was executed.
<img src="/images/fiestaEKnaveo.png" alt="naveo" /></li>
</ul>
</li>
<li><strong>hags5()</strong>
<ul>
<li>Purpose: Deliver Java FX exploit for Java v6.3-7.22 from hxxp://digiwebname.in/6ktpi5xo/1b9a9eecb34c4c045b0c555a0b5e545a03510a5a0d075558045601570a57575a</li>
<li>Applicable to 38NTRGDFQKR-PC: <strong>No.</strong></li>
<li>This was not available in the packet capture.</li>
</ul>
</li>
<li><strong>glumw9()</strong>
<ul>
<li>Purpose: Deliver malicious Java Applet exploit for Java >6 from hxxp://digiwebname.in/6ktpi5xo/55fdd7ebca026cab5447075f560c545b0706555f5055555900015e525705575b</li>
<li>Applicable to 38NTRGDFQKR-PC: <strong>Yes.</strong> At the time of the incident, the network artifacts reflect the workstation was running Java 1.6 and this exploit is targeted at anything below version 6.
<img src="/images/fiestaEKglumw9.png" alt="glumw9" /></li>
</ul>
</li>
<li><strong>chadvs()</strong>
<ul>
<li>Purpose: Deliver malicious Silverlight exploit for Builds 4.0.50401.00 through 5.1.20125.0 from http://digiwebname.in/6ktpi5xo/39e112e34c7d1c884055130a0309540a010a560a05505508060d5d070200570a</li>
<li>Applicable to 38NTRGDFQKR-PC: <strong>Yes.</strong> At the time of the incident, the workstation was running 4.0.6053.1.
<img src="/images/fiestaEKchadvs.png" alt="chadvs" /></li>
</ul>
</li>
<li><strong>bugs5()</strong>
<ul>
<li>Purpose: Deliver JavaScript based exploit for Internet Explorer versions 8 through 10 from hxxp://digiwebname.in/6ktpi5xo/4d0a65349d0e9f375d015c5a040e020d0657035a0257030f015008570507010d</li>
<li>Applicable to 38NTRGDFQKR-PC: <strong>Yes.</strong> User was running IE 8 at the time of the attack.
<img src="/images/fiestaEKbugs5.png" alt="bugs5" /></li>
</ul>
</li>
<li><strong>robst()</strong>
<ul>
<li>Purpose: Deliver Adobe Acrobat AcroPDF ActiveX control exploit for version 8-8.21,9.3-10 from http://digiwebname.in/6ktpi5xo/7d0d7c94be7afa7a5b0d525f0558080d0557035f0301090f0250085204510b0d</li>
<li>Applicable to 38NTRGDFQKR-PC: <strong>¯\_(ツ)_/¯.</strong> This one is a bit of a mystery. Despite the user not having the correct version of Adobe Acrobat AcroPDF, the exploit is still requested in TCP stream 32.
<img src="/images/fiestaEKmystery1.png" alt="PDF Mystery" />
<img src="/images/fiestaEKmystery2.png" alt="PDF Mystery" />
Unless I screwed something up, which happens…often, 910 does not meet this logic criteria: (adobeVer >= 800 and adobeVer < 821) or (adobeVer >= 1000 and adobeVer < 931).</li>
</ul>
</li>
</ul>
<h3 id="stage-4-exploitation"><strong>Stage 4: Exploitation</strong></h3>
<p><strong>hyepksam259.swf</strong></p>
<p>The first of the five leveraged exploits in the EK, hyepksam259.swf is a Shockwave Flash file that exploits <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2014-0569">CVE-2014-0569</a> Adobe Flash Player casi32 Integer Overflow Remote Code Execution Vulnerability.</p>
<p>TCP stream 30 shows the workstation requesting hxxp://digiwebname.in/6ktpi5xo/3830948c194842760701040b0b0f095a010b000b0d560858060c0b060a060a5a;118800;94 with the “18800;94” containing version information for Shockwave. The hyepksam259.swf md5:808bb909e98f93c38f54b6cfc9702520 is delivered to the endpoint.
JPEXS was used to review the obfuscated and encrypted ActionScript.
<img src="/images/fiestaEKswf.png" alt="PDF Mystery" /></p>
<ul>
<li>yakspi(): XORs two variables</li>
<li>briols[]: Array of Encrypted Action Script</li>
<li>girdq(): Loads Decrypted Action Script</li>
</ul>
<p>The purpose of this SWF is to generate a second SWF that downloads (TCP stream 31) and executes an encrypted portable executable: [MD5 72c2c343ebea67767de167aaf254a91d].</p>
<p><strong>JavaScript</strong></p>
<p>The second of the five leveraged exploits in the EK, presents the user with a page full of obscure words. The JavaScript embedded on this page uses the exact same encryption as the previous one; using “I450S+bxX=9UjpAG7fNaq3sd2M61Ze8LkcJRhg” as the encryption key. The only difference being the function name was “viasw” instead of “boomp”.
<img src="/images/fiestaEKjsview.png" alt="JS Exploit" />
I find that bit of trivia interesting because it speaks to how the kit was built and how much actual unique code I need to reverse. Also, I noticed many of the variable names in these scripts are 4 letter English words with 1 or 2 extra characters on the end…</p>
<p>The HTML document body contains two div elements “soiln” and “debtx”, each containing encoded objects. Chrome’s developer tools we used to deobfuscate the bulk of the code.</p>
<ul>
<li>soiln - decodes to contains 2907 bytes of base64ed data with Shannon entropy of 7.7 which is consistent with encrypted or compressed data.</li>
<li>debtx - contains script and 2197 bytes of encoded data with a Shannon entropy of 5.8 which is consistent with encoded scripts.</li>
</ul>
<p>This code is densely obfuscated and I could dig deeper on this later if I get really bored.</p>
<p><strong>buvyoem41.pdf</strong></p>
<p>The third package delivered is a PDF containing an exploit for CVE- 2010-0188, Unspecified vulnerability in Adobe Reader and Acrobat 8.x before 8.2.1 and 9.x before 9.3.1. In TCP stream 32 we can see the buvyoem41.pdf being delivered from the landing page request.
<img src="/images/fiestaEKPDFDumper.png" alt="PDF Dumper" />
This PDF document presents with repeating nonsensical sentences and contains 3 notable objects:</p>
<ul>
<li>Object 9: Obfuscated JavaScript containing more Base64 encoded encrypted JavaScript that calls Object 10 via Object 6.
<ul>
<li>Interestingly enough, the JavaScript in the PDF uses the same “I450S+bxX=9UjpAG7fNaq3sd2M61Ze8LkcJRhg” for a key but using “polyu” as decrypt function.</li>
</ul>
</li>
<li>Object 10: Minisets of Base64 encoded shellcode.
When loaded, this PDF downloads (TCP stream 34) and executes an encrypted portable executable: [MD5 72c2c343ebea67767de167aaf254a91d].</li>
</ul>
<p><strong>dszohrfb90.xap</strong></p>
<p>The forth package delivered is a Microsoft Silverlight file containing an exploit for CVE-2013-0074.A: Double Dereference Vulnerability. Using 7zip to extract the contents, we can see the following files within:</p>
<ul>
<li>AppManifest.xaml
<ul>
<li>Windows markup file that references kagfhwyr720.dll</li>
</ul>
</li>
<li>kagfhwyr720.dll
<ul>
<li>.NET PE file that decrypts ward7w using an XOR key of 88 and then loads shellcode from the “gall” applet parameter from the landing page.
<img src="/images/fiestaEKILSpy.png" alt="IL Spy" /></li>
</ul>
</li>
<li>ward7w
<ul>
<li>.NET DLL titled “goat” with 5 sections: App, coed, dido, part, vote</li>
<li>Contains obfuscated code distributed across various functions and encoded in Base64</li>
</ul>
</li>
</ul>
<p>When injected into the landing page this Silverlight file downloads (TCP stream 36) and executes the same encrypted portable executable: [MD5 72c2c343ebea67767de167aaf254a91d].</p>
<p><strong>syvwkahx581.jar</strong></p>
<p>The final exploit delivered was a Java JAR file that exploits CVE-2012-0507, a vulnerability in the Java Runtime Environment related to Concurrency. I didn’t spend time on this exploit because it was requested by the landing page in tcp.stream 41, after the host was already compromised, reflected by the POST request in tcp.stream 38.</p>
<h3 id="stage-5-installation"><strong>Stage 5: Installation</strong></h3>
<p>Each of the exploits in this kit delivers the same portable executable, Punto Switcher MD5: 72c2c343ebea67767de167aaf254a91d. Googling Puntu Switcher reveals it is a questionably legitimate Russian software used to switch keyboard layout between languages. Analysis of this sample suggests that this software was hollowed and used to host malicious code.</p>
<p>Notable characteristics:</p>
<ul>
<li>Persistence
<ul>
<li>Copied itself to %TEMP%</li>
<li>Established with HKCU\SOFTWARE\Microsoft\Windows\CurrentVersion\Run</li>
</ul>
</li>
<li>Exfiltration
<ul>
<li>Upon execution this malware retrieves the following information from the target system:
<ul>
<li>select * from win32_SystemEnclosure</li>
<li>select * from win32_ComputerSystem</li>
<li>select * from win32_BaseBoardF</li>
<li>select * from win32_PhysicalMedia</li>
<li>select * from win32_DiskDrive</li>
<li>select * from win32_CDROMDrive</li>
<li>select * from win32_OnBoardDevice</li>
<li>select Name, ExecutablePath from win32_Process</li>
<li>select * from win32_OperatingSystem</li>
<li>select * from win32_Processor</li>
<li>select * from win32_BIOS</li>
<li>select * from win32_VideoController</li>
<li>select * from win32_DisplayConfiguration</li>
</ul>
</li>
<li>This data is encrypted with a low entropy cipher and submitted as an HTTP POST request to 209.239.112.229:80.
<ul>
<li>Data is given human readable headers such as “\n== Processes [0] ==\n”</li>
<li>Due to time constraints, my analysis did not yield the exact encryption routine however I believe this traffic is decryptable with the artifacts provided for the following reasons:
<ul>
<li>the traffic always starts with 0x6846</li>
<li>low entropy of traffic</li>
<li>the large number of matching bytes across multiple instances of the traffic</li>
</ul>
</li>
</ul>
</li>
</ul>
</li>
</ul>
<h4 id="clean-up">Clean up</h4>
<p>Luckily, the C2 site (209.239.112.229) was down at the time of the incident and the command and control channel was not established with 38NTRGDFQKR-PC.</p>