Output authenticity

Tue, 25 Aug 2026 00:00:00 +0000

Part of my AI Security Engineering series, a local email-to-calendar agent I build, then attack, then harden. If you have not set up the lab yet, start with Set up your lab. The lessons are on GitHub, and the agent itself lives at t0ul/emaildrop.

The output has to be checkable too

The last post signed the data coming in. This one signs the artifacts going out, and closes the governance chapter by turning the same provenance check outward. The agent produces things people act on: a calendar file you import, a summary you read and trust, an action you approve based on what it told you. All of that rests on an assumption that is almost never stated, that a thing which looks like the agent’s output actually is. Once an agent’s output has authority, that assumption is a target.

Provenance on t0ul

Output authenticity

The output has to be checkable too