Agentic Commerce Bench: Measuring Fraud Detection for Agents That Spend Money
AI agents now hold spend authority and settle payments without per-action human confirmation. The resulting loss is often not a security failure: a counterparty with the correct domain, the correct settlement address and a genuinely delivered service can charge more than it should, and no check keyed on identity will see it. We present three artefacts for measuring and reducing that loss. First, a taxonomy of agentic commerce fraud that separates five observation levels (agent reasoning, wire, settlement rail, counterparty, principal) from the request-level and history-level evidence available at each, and records which levels can observe which attacks. Second, Agentic Commerce Bench (ACB...
| Authors | Ankit Srivastava, Debjyoti Paul |
|---|---|
| Primary category | cs.CR |
| Published | 27 September 2026 |
| Last updated at source | 27 September 2026 |
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