The author introduces USAP, a system designed to improve the verifiability of AI security verdicts by enforcing an "evidence gate" pattern. This pattern requires every verdict to be backed by at least one resolvable source, such as a CVE, an external feed, or an operator artifact. This strict requirement leads to three key outcomes: connectors must be abstract to accommodate different security tools, numerical scores must be directly computable from cited evidence rather than narrated, and the system cannot grade itself against its own outputs. USAP is open-source and can be run as an MCP server or integrated into existing model prompts. AI
IMPACT Enhances trust and reliability in AI security analysis by ensuring verdicts are grounded in verifiable evidence.
RANK_REASON The item describes a new open-source tool for AI security analysis.
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