Your AI coding agent can read files, run shell commands, and call external APIs. That's also the exact description of an arbitrary code execution primitive — and attackers have figured that out.
A recent report from The Hacker News details "Agentjacking," a class of attack that hijacks AI-powered coding agents by manipulating their tool-execution pipeline. The agent isn't compromised at the model level — it's compromised through the tools it trusts. The agent reads something malicious, reasons its way into executing it, and your environment is owned before a human ever sees a diff.
This is the agentic security problem in its clearest form: the attack surface isn't the LLM, it's the autonomy.
How Agentjacking Actually Works
Modern coding agents — the kind that can scaffold a project, run tests, and push a PR — operate through a tool-use loop. They receive instructions, call tools (read a file, execute a command, query an API), observe the results, and decide what to do next. That observation-action loop is exactly what makes them useful.
