Proof over Persuasion
AI agents now hold money, set prices and take orders, and anyone can talk to them. This is a public record of agents that were talked into moving value, graded by evidence, and the design principles that would have stopped them.
Kept by Gunjit Mittal at Monetal Labs.
If they needed to break in, it’s security.
If they only needed the agent to believe them, it’s design.
Five of the six losses on record involved no stolen key and no broken code. The agent did what it was told. That makes them design problems: where authority lives, what counts as an instruction, and what a conversation is allowed to change.
Incident analysis 001
An attacker drained at least $150,000 in tokens from a crypto wallet linked to Grok, xAI’s chatbot. No private key was stolen and no smart contract was broken. One agent’s reply became another agent’s command.
- Published
- October 27, 2026
Read the analysis
Design Principles for AI Agents
v0.2, released October 19, 2026. 5 supported, 6 emerging.
Read the principles
How the work is built
An incident
A documented case of an AI agent with authority being gamed, taken from public sources only.
A register entry
Graded A to D by the strength of its evidence, and mapped to the principles that were missing.
A principle
Each entry strengthens a principle, refines it or reveals a new one. A principle’s status follows the evidence.
An analysis
One entry at a time: what happened, the design gap, the principle that would have closed it, and its cost.
Who keeps this
Monetal Labs is run by Gunjit Mittal. His background is in data platforms: access controls, semantic layers, data quality, and reconstructing what a system knew at a point in time. That is the evidence an agent leaves behind when it moves money.
If your company runs an AI agent that can move money or make commitments, or you’ve seen one gamed, he’d like to hear from you.
About the workMessage him on LinkedIn