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See currentAI Audit of an AI-Agent Protocol Found High-Severity Trust Flaws
minia2a · August 2026 · AI Contract Audit · Static Scan
We audited a live, decentralized AI-agent orchestration protocol. Our AI found high-severity trust flaws in the task lifecycle.
High-severity findings — details under responsible disclosure
HIGHTask-completion trust gap
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.
HIGHDispute-window logic
A second flaw in the dispute/deadline logic can lock in a payout before a legitimate dispute can be raised.
Why this matters for agent economies
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.
Full report available to project owners. If your protocol is affected, contact us for the complete vulnerability report — before an agent exploits it.
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AI Deep Audit — $200 (business-logic & economic flaws + responsible disclosure)
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Static Scan — $2 (10 vulnerability patterns)
AI audit is probabilistic — may miss vulnerabilities or report non-issues. Treat as guidance, not proof.