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Enforce compliant AI-to-data access with masking, policy controls, and audit trails.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Aegis" yet — see the docs or source repo.
Design a compliance access layer for my MCP setup: AI agents need to query a customer database, but field access must be role-based, phone numbers and national IDs must be masked, and full audit logs must be recorded. Provide policy rules, access flow, and sample configuration.
A compliance design including access controls, sensitive data masking, audit logging, and sample configuration.
I have multiple AI agents for support, analytics, and operations. Help me define data access policies: support can only view limited customer fields, analytics can access only aggregated data, and operations cannot read any PII. Output a clear policy matrix and enforcement rules.
A role-based data permission matrix and enforceable policy rule definitions.
Help me design an MCP-focused audit plan to track what data AI agents accessed, which policies were triggered, which requests were denied, and how to generate compliance audit reports. Include recommended log fields.
A complete audit design covering access logs, policy hits, denied events, and audit report structure.
Audit AI agent permissions by scanning credential, injection, and reach risks.
Secure AI agents locally with cost controls, injection blocking, and action approvals.
Gives AI coding agents deterministic security rules from a project's threat model.
Keep AI coding agents architecture-aware, verified, drift-checked, and safer over long tasks.
Add cited compliance checks and standards mapping to AI assistants.
Audit MCP servers and AI packages for security and supply chain risks.