<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Red-Team on Riccardo Ancarani</title><link>https://riccardoancarani.github.io/tags/red-team/</link><description>Recent content in Red-Team on Riccardo Ancarani</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 21 Mar 2020 00:00:00 +0000</lastBuildDate><atom:link href="https://riccardoancarani.github.io/tags/red-team/index.xml" rel="self" type="application/rss+xml"/><item><title>Attacking Insecure ELK Deployments</title><link>https://riccardoancarani.github.io/2020-03-21-attacking-insecure-elk-deployments/</link><pubDate>Sat, 21 Mar 2020 00:00:00 +0000</pubDate><guid>https://riccardoancarani.github.io/2020-03-21-attacking-insecure-elk-deployments/</guid><description>&lt;h1 id="introduction"&gt;Introduction&lt;/h1&gt; &lt;p&gt;Nowadays, we see a continuous increase of the adoption of the Elasticsearch Logstash Kibana (ELK) stack for security monitoring purposes.
The functionalities of the ELK stack fit nicely the purpose of a SIEM; in fact, within few minutes it is possible to spin up a cluster and deploy the data collectors on the endpoints.&lt;/p&gt;
&lt;p&gt;Considering the open source nature of the Elastic project and the presence of ingestors like &lt;a href="https://www.elastic.co/downloads/beats/winlogbeat" target="_blank" rel="noopener"&gt;Winlogbeat&lt;/a&gt; , its increase in popularity is not surprising.&lt;/p&gt;</description></item><item><title>Extending BloodHound</title><link>https://riccardoancarani.github.io/2020-02-06-extending-bloodhound/</link><pubDate>Thu, 06 Feb 2020 00:00:00 +0000</pubDate><guid>https://riccardoancarani.github.io/2020-02-06-extending-bloodhound/</guid><description>&lt;p&gt;This series of posts was inspired by porterhau5&amp;rsquo;s work that can be found here: &lt;a href="https://porterhau5.com/blog/extending-bloodhound-track-and-visualize-your-compromise/" target="_blank" rel="noopener"&gt;Extending BloodHound: Track and Visualize Your Compromise&lt;/a&gt; .&lt;/p&gt;
&lt;h3 id="1-the-problem"&gt;1. The Problem&lt;/h3&gt; &lt;p&gt;In a standard Active Directory assessment, a fundamental phase is the analysis of Group Policy Objects (GPOs). Usually, this activity is aimed at identifying the following:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Opportunities for lateral movement via misconfigurations of remote access policies and UAC&lt;sup id="fnref:1"&gt;&lt;a href="#fn:1" class="footnote-ref" role="doc-noteref"&gt;1&lt;/a&gt;&lt;/sup&gt;;&lt;/li&gt;
&lt;li&gt;Misconfigurations that could allow further compromise, such as lack of SMB signing;&lt;/li&gt;
&lt;li&gt;Password policies;&lt;/li&gt;
&lt;li&gt;Privilege Assignment;&lt;/li&gt;
&lt;li&gt;Local group membership.&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&amp;hellip;and much more.
The process of parsing GPOs is often tedious and very time consuming. Tools like Grouper2&lt;sup id="fnref:2"&gt;&lt;a href="#fn:2" class="footnote-ref" role="doc-noteref"&gt;2&lt;/a&gt;&lt;/sup&gt; can drastically reduce the required time, but the volume of the output is still quite considerable.&lt;/p&gt;</description></item></channel></rss>