Suggesting Agent Trust Bench for the Benchmarks & Datasets section.
Agent Trust Bench -- https://agent-trust-bench.algovoi.co.uk
Live adversarial benchmark for AI agents that handle x402/A2A payment flows. 138 profiles across 30 threat categories, mapped to OWASP LLM Top-10 (LLM01 Prompt Injection, LLM06 Sensitive Info Disclosure, LLM07 Insecure Plugin Design, LLM08 Excessive Agency, LLM09 Overreliance, plus FATF financial-regulation scenarios).
What makes it distinct from static datasets: the bench is a live endpoint. Agents make real HTTP calls against adversarial payment challenges (fake-signed, $1 USDC cap enforced server-side) and pass or fail based on their actual decisions -- not pattern matching against a static corpus.
Three reference personas (safe / aggressive / unbounded) for cross-LLM or cross-framework comparison. Machine-readable discovery at:
GET https://agent-trust-bench.algovoi.co.uk/.well-known/x402.json
MIT-licensed runner. No account required. 30-day responsible-disclosure window for profile vulnerabilities.
Suggesting Agent Trust Bench for the Benchmarks & Datasets section.
Agent Trust Bench -- https://agent-trust-bench.algovoi.co.uk
Live adversarial benchmark for AI agents that handle x402/A2A payment flows. 138 profiles across 30 threat categories, mapped to OWASP LLM Top-10 (LLM01 Prompt Injection, LLM06 Sensitive Info Disclosure, LLM07 Insecure Plugin Design, LLM08 Excessive Agency, LLM09 Overreliance, plus FATF financial-regulation scenarios).
What makes it distinct from static datasets: the bench is a live endpoint. Agents make real HTTP calls against adversarial payment challenges (fake-signed, $1 USDC cap enforced server-side) and pass or fail based on their actual decisions -- not pattern matching against a static corpus.
Three reference personas (safe / aggressive / unbounded) for cross-LLM or cross-framework comparison. Machine-readable discovery at:
MIT-licensed runner. No account required. 30-day responsible-disclosure window for profile vulnerabilities.