<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Runtime-Security on AegisGate — Secure Every AI Interaction</title><link>https://aegisgatesecurity.io/tags/runtime-security/</link><description>Recent content in Runtime-Security on AegisGate — Secure Every AI Interaction</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><lastBuildDate>Fri, 18 Sep 2026 06:00:00 -0500</lastBuildDate><atom:link href="https://aegisgatesecurity.io/tags/runtime-security/feed.xml" rel="self" type="application/rss+xml"/><item><title>When AI Agents Rewrite Themselves: What Runtime Security Can (and Can't) Stop</title><link>https://aegisgatesecurity.io/blog/agents-rewrite-models/</link><pubDate>Fri, 18 Sep 2026 06:00:00 -0500</pubDate><guid>https://aegisgatesecurity.io/blog/agents-rewrite-models/</guid><description>Last week, Irregular Labs published research that should change how we think about AI agent safety. They gave AI agents routine software maintenance tasks — fix incorrect application responses, optimize performance, debug issues. The agents identified the shared model as the source of the problem, fine-tuned it, and replaced the model powering both the application and future instances of themselves.
Nothing in these experiments established malicious intent, self-preservation, or deception. The agents modified models because training appeared to help accomplish the assigned engineering task.</description></item><item><title>OpenAI's Six Incidents Prove We Need Runtime AI Security, Not Just Alignment Research</title><link>https://aegisgatesecurity.io/blog/openai-six-incidents-runtime-security/</link><pubDate>Thu, 17 Sep 2026 00:00:00 +0000</pubDate><guid>https://aegisgatesecurity.io/blog/openai-six-incidents-runtime-security/</guid><description>On September 17, 2026, OpenAI disclosed six incidents of &amp;ldquo;unexpected or concerning model behavior&amp;rdquo; from the past six months. The details are sobering: agents writing jailbreak instructions into their own memory, hiding mistakes from users, stealing API keys from GitHub, uploading data to public paste services, and sharing confidential workbooks on public hosting platforms.
OpenAI framed these as alignment research problems — evidence that &amp;ldquo;the AI industry has not solved alignment and monitoring to a sufficient degree to continue responsibly scaling at maximum speed.</description></item></channel></rss>