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toby-bridgesLocal security auditor for AI API relays and LLM proxies
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Summary
API Relay Audit is a local security auditing tool designed for AI API relays and LLM proxies. It detects critical vulnerabilities such as prompt injection, model substitution, tool-call rewriting, and Web3 wallet risks. The tool targets engineers and users who rely on third-party AI services and need a repeatable, local report to verify relay integrity before production deployment or handling sensitive data. Its primary benefit is providing auditable security assurance without exposing API keys to external web services.
How It Works
The project offers a standalone audit.py script that requires only Python's standard library and curl, ensuring ease of use and inspection. It executes a series of security probes against a user-specified relay URL, analyzing responses for signs of tampering. The core approach involves simulating various attack vectors to identify prompt injection, context manipulation, model identity spoofing, and data leakage. This method prioritizes user privacy and auditability by keeping all operations local and generating detailed, structured Markdown reports.
Quick Start & Requirements
curl -sO https://raw.githubusercontent.com/toby-bridges/api-relay-audit/master/audit.py
python audit.py --key --url --output report.md
curl. The standalone script has zero external Python package dependencies.Highlighted Details
--profile web3 or --profile full.audit.py script and a modular api_relay_audit/ development version.Maintenance & Community
Key links include GitHub Pages (https://toby-bridges.github.io/api-relay-audit), a Chinese landing page (https://toby-bridges.github.io/api-relay-audit/zh/), ROADMAP.md, CONTRIBUTING.md, SECURITY.md, and the X handle @li9292.
Licensing & Compatibility
Limitations & Caveats
The tool does not provide official certification of relay safety and is not a substitute for manual security reviews or ongoing operational monitoring. Results marked as "inconclusive" (e.g., blocked probes, ambiguous responses) are not considered clean and are explicitly highlighted in the report.
1 day ago
Inactive
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