# Security Considerations

## Threat modeling and risk assessment
- Tampering vectors: bytecode modification, function replacement, module injection/removal, import hook manipulation, monkey-patching.
- Risks: baseline poisoning, TOCTOU between checks, privilege constraints for memory mapping.

## Authentication and authorization mechanisms
- N/A at library level (not an auth system). Recommend integrating with application authN/Z for response policies and auditing.

## Data encryption and privacy policies
- Baseline resides in-process; optional save/export are plaintext by default—encrypt and protect at rest if persisted.

## Secure coding practices
- Prefer least privilege for deployment.
- Maintain strict whitelists to avoid benign dynamics triggering alerts.
- Validate and sanitize callbacks; do not trust untrusted event data.

## Vulnerability mitigation
- Use `ProtectionLevel.HIGH/PARANOID` for sensitive workloads.
- Combine with other defenses: code signing, container/AppArmor/SELinux, secrets hygiene, supply-chain controls.

References: `README.md` (Security Model/Considerations), `cynapse/models.py`.
