I scanned my AI agent framework for destructive/consequential actions, and wow
Researchers scanned 25 AI agent frameworks, analyzing 23,476 files, to identify consequential actions lacking authorization checks. They discovered 30 such actions across categories like data loss, execution, and network egress, and refined their scanner to eliminate false positives. The study highlights that many agent tools validate inputs without verifying caller permissions, and notes limitations of static analysis for comprehensive coverage.
- ▪The scan covered 25 repositories and identified 30 consequential actions without proper authorization checks.
- ▪Common risky actions included workspace purging, SQL table drops, and custom network notifications.
- ▪Initial scanner precision was 81%, but after three fixes it achieved 100% precision on the identified findings.
- ▪The most exposed function was purge_workspace in app/tools.py, reachable via the @mcp.tool() decorator.
- ▪The authors emphasize that validation does not equal authorization and that static analysis cannot guarantee full coverage.
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Research noteJuly 2026Apache 2.0 Your agent can already do things nobody authorised. We scanned 25 AI agent frameworks — 23,476 files — looking for one specific thing: a consequential action that a model can reach, with a parameter the model controls, and no authorisation check on the path. We found 30. We also found 12 false positives in our own scanner, and fixed them before publishing this. ~/your-agent $ pipx run actenon-scan scan . Your agent can take 7 consequential actions without an authorisation check.
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