We audited a live, decentralized AI-agent orchestration protocol. Our AI found high-severity trust flaws in the task lifecycle.
We found a flaw where an assigned party can finalize a task and receive payout with insufficient verification of completed work. In an agent economy, this is the central fake-completion fraud risk.
Specific exploit details are withheld under responsible disclosure. Project owners: contact for full report.
A second flaw in the dispute/deadline logic can lock in a payout before a legitimate dispute can be raised.
As AI agents autonomously earn, protocols must prevent fake-completion fraud. This pattern — an actor self-verifying its own work — is the central trust problem in agent-to-agent economies. Our AI auditor flagged it in minutes.
These are real business-logic flaws in a real, current AI-agent protocol — exactly what static scanners miss.