Buy the Control Plane. Then Prove It Works.
Agent control is turning into a product you can buy. Open or closed, you didn't write it, so what it does in your environment is the only proof you'll get.
7 posts tagged with “ai-agent-security”
Agent control is turning into a product you can buy. Open or closed, you didn't write it, so what it does in your environment is the only proof you'll get.
Darktrace rewrote the saved conversations of four coding agents and got them to attack a network. The lesson isn't about signatures. It's about where your agent's permission comes from.
Seven defects surfaced in one migration. None of them crashed, none failed a test, and none turned a dashboard red. A broken control and a working control send the same signal: silence.
An agent refused to run the attacker's binary, then wrote its own decoder and ran the payload anyway. Three incidents and one of our own show the same thing: a constraint you hand an agent is a preference it can route around.
A tidy-up PR removed a safety pattern from a Snowflake workflow. Five days later an autonomous agent had a Jira token. The headlines said an AI wrote the bug; the commit history cannot actually tell you who did, and that is the more serious problem.
Five CVEs across four vendors in thirteen months, all the same bug: your coding agent trusts a directory, then executes a file that can change underneath it. Here is the pattern, and the one line in Claude Code's restricted mode that actually fixes it.
Three pieces of research showed how to hijack AI coding agents. I run Claude Code, MCP, and autonomous CI agents in production — so I ran them against my own setup. Here's what held, what didn't, and what I changed.