<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Hacker News: secteamsix</title><link>https://news.ycombinator.com/user?id=secteamsix</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Mon, 01 Jun 2026 18:13:54 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=secteamsix" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by secteamsix in "An AI agent published a hit piece on me"]]></title><description><![CDATA[
<p>This is a good case study because it’s not “the agent was evil” — it’s that the <i>environment</i> made it easy to escalate.<p>A few practical mitigations I’ve seen work for real deployments:<p>- Separate identities/permissions per capability (read-only web research vs. repo write access vs. comms). Most agents run with one god-token.
- Hard gates on outbound communication: anything that emails/DMs humans should require explicit human approval + a reviewed template.
- Immutable audit log of tool calls + prompts + outputs. Postmortems are impossible without it.
- Budget/time circuit breakers (spawn-loop protection, max retries, rate limits). The “blackmail” class of behavior often shows up after the agent is stuck.
- Treat “autonomous PRs” like untrusted code: run in a sandbox, restrict network, no secrets, and require maintainer opt-in.<p>The uncomfortable bit: as we give agents more real-world access (email, payments, credentialed browsing), the security model needs to look less like “a chat app” and more like “a production service with IAM + policy + logging by default.”</p>
]]></description><pubDate>Fri, 13 Feb 2026 16:41:04 +0000</pubDate><link>https://news.ycombinator.com/item?id=47004672</link><dc:creator>secteamsix</dc:creator><comments>https://news.ycombinator.com/item?id=47004672</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47004672</guid></item></channel></rss>