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    <title>Agent on @Unc1e</title>
    <link>https://www.unc.la/en/tags/agent/</link>
    <description>Recent content in Agent on @Unc1e</description>
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      <title>You Bought the Hands, Not the Brain: After Analyzing Burp AT, I Built an Open-Source Burp MCP</title>
      <link>https://www.unc.la/en/posts/penetration/burp-at-brain-hand-open-source-mcp/</link>
      <pubDate>Wed, 12 Aug 2026 00:20:00 +0800</pubDate>
      <guid>https://www.unc.la/en/posts/penetration/burp-at-brain-hand-open-source-mcp/</guid>
      <description>Burp AT proves that penetration testing can be handed to AI, but it locks the model in the cloud and suffers from approval fatigue in production. I analyzed its protocol, followed the official front door, and built an open-source burp-mcp-server — filling the gaps that make or break a red-team automation loop.</description>
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    <item>
      <title>Agents Can Now Take Action—Security Can&#39;t Stay in the Conversation: Runtime Design at the Action Boundary</title>
      <link>https://www.unc.la/en/posts/penetration/agents-next-problem-is-action-boundary/</link>
      <pubDate>Sun, 02 Aug 2026 10:50:39 +0800</pubDate>
      <guid>https://www.unc.la/en/posts/penetration/agents-next-problem-is-action-boundary/</guid>
      <description>&lt;p&gt;Lately I&amp;rsquo;ve been doing more and more AI red teaming: half the time thinking about how to attack Agents, and the other half thinking about:&lt;/p&gt;
&lt;p&gt;once the attacks are done, what should real-world defense actually look like?&lt;/p&gt;
&lt;p&gt;I&amp;rsquo;ve written a local-first Agent Runtime Guard (ARG) myself, and I&amp;rsquo;ve also taken apart Microsoft&amp;rsquo;s newly open-sourced Agent Governance Toolkit (AGT). After taking both apart, the conclusion is actually quite clear:&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Agent runtime protection is, in essence, the &amp;ldquo;firewall&amp;rdquo; of the LLM era&lt;/strong&gt;. Whenever I mention &amp;ldquo;firewall&amp;rdquo;—a word that has been beaten to death—I want to laugh. Still, this is decidedly not another layer of prompt rhetoric, nor is it old IAM renamed. What it intercepts is the segment where &amp;ldquo;the model&amp;rsquo;s intent has already formed, but the side effects haven&amp;rsquo;t happened yet&amp;rdquo;—the command hasn&amp;rsquo;t been exec&amp;rsquo;d, the keys haven&amp;rsquo;t been read, the email hasn&amp;rsquo;t been sent, no HTTP has left the network.&lt;/p&gt;</description>
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    <item>
      <title>Reverse OpenRouter</title>
      <link>https://www.unc.la/en/posts/penetration/iy7k17ehlduoblsm/</link>
      <pubDate>Sun, 26 Apr 2026 12:10:14 +0800</pubDate>
      <guid>https://www.unc.la/en/posts/penetration/iy7k17ehlduoblsm/</guid>
      <description>&lt;p&gt;Reverse-proxy the OpenRouter AI API through an overseas server to work around regional access restrictions.&lt;/p&gt;
&lt;h2 id=&#34;background-scqa&#34;&gt;Background (SCQA)&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;S - Situation&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;Overseas AI services (image generation, chat, etc.) are typically accessed through aggregator platforms like OpenRouter that offer a unified API, compatible with the OpenAI SDK.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;C - Complication&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;These services impose access restrictions on mainland China — if the requesting source IP is identified as originating from within China, service is refused outright.&lt;/p&gt;</description>
    </item>
    <item>
      <title>Stuffing OpenAI&#39;s Privacy Filter Model into the Red Team Toolchain</title>
      <link>https://www.unc.la/en/posts/penetration/openai-privacyfilter-into-redteam/</link>
      <pubDate>Sat, 25 Apr 2026 11:11:28 +0800</pubDate>
      <guid>https://www.unc.la/en/posts/penetration/openai-privacyfilter-into-redteam/</guid>
      <description>&lt;p&gt;&lt;img loading=&#34;lazy&#34; referrerpolicy=&#34;no-referrer&#34; src=&#34;https://cdn.nlark.com/yuque/0/2026/png/166008/1777302701535-625c20f6-3b1b-4d69-8060-c6cfaca61d29.png&#34;&gt;&lt;/p&gt;
&lt;blockquote&gt;
&lt;p&gt;Red team security tooling — rebuilding OpenAI&amp;rsquo;s Privacy Filter into an HTTP gateway for structured PII&lt;/p&gt;
&lt;p&gt;extraction&lt;/p&gt;
&lt;/blockquote&gt;
&lt;p&gt;OpenAI open-sourced a small model called Privacy Filter that can identify PII such as names, emails, phone numbers, and addresses from unstructured text.&lt;/p&gt;
&lt;p&gt;&lt;img loading=&#34;lazy&#34; referrerpolicy=&#34;no-referrer&#34; src=&#34;https://cdn.nlark.com/yuque/0/2026/png/166008/1777301197503-5cec4ca4-265a-4705-82b4-c2ca7e2d84e0.png&#34;&gt;&lt;/p&gt;
&lt;p&gt;I spent one evening turning it into an HTTP gateway service, running on an NVIDIA L20, with dual-process inference peaking at 81 RPS and GPU utilization pushed to 98%.&lt;/p&gt;</description>
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