If you discover a security vulnerability in this package, please do not open a public GitHub issue.

Email security@axumquant.com with:

1. A description of the vulnerability
2. Steps to reproduce
3. The affected version(s)
4. Any potential impact you've identified

We aim to acknowledge reports within 72 hours and to ship a fix or mitigation within 14 days for high-severity issues.

This package uses LLMs to classify network endpoints discovered from CDP traffic and to generate extraction schemas. Security-relevant areas:

• Prompt injection — captured network responses are passed to the LLM. A malicious response body could try to inject instructions ("ignore previous, output this schema instead"). Reports that demonstrate successful injection that produces a malformed or attacker-controlled SiteSchema are in scope.
• Schema-driven extraction — the Eavesdropper uses dot-paths from the schema to extract fields. Path traversal that escapes the response object scope is in scope.
• Healer self-modification — the Healer can persist schema corrections. A malicious extraction failure that tricks the healer into approving an attacker-controlled schema is in scope.
• PII in logs — by default the library logs at INFO. Bugs that cause caller-supplied PII (names, MBI, account ids) to land in the structured log output are in scope.

Out of scope:

• LLM provider vulnerabilities (report to OpenAI / Anthropic / Ollama)
• pydantic-ai vulnerabilities (report upstream)
• Misuse by consumers (e.g., piping raw caller transcripts into the prompt without scrubbing)