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Audit AI agent permissions by scanning credential, injection, and reach risks.
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.
Use aegis to scan our AI agent configuration and toolchain. Check for exposed credentials, prompt injection paths, and whether the agent can reach systems or data beyond expectations. Return a risk list and remediation advice.
A severity-ranked audit report listing credential, injection, and reach issues with remediation steps.
Before release, run a rapid security review with aegis on this newly deployed AI assistant. Identify high-risk permissions, possible injection entry points, and unnecessary external connections, then conclude whether it is ready to launch.
A pre-release check result with blockers, warnings, and a launch recommendation.
Use aegis to analyze this AI agent’s current permissions and reachable resources. Find over-permissioning, lateral access, and sensitive data exposure risks, and suggest a least-privilege configuration.
A least-privilege recommendation report explaining what access should be reduced and how to adjust it.
Secure AI agents locally with cost controls, injection blocking, and action approvals.
Enforce compliant AI-to-data access with masking, policy controls, and audit trails.
Audit MCP servers and AI packages for security and supply chain risks.
Audit MCP configs for exposed access, secrets, models, and compliance AI-BOMs.
Gives AI coding agents deterministic security rules from a project's threat model.
Automate red-teaming and reliability audits for AI agents through MCP.