Local-first security check for AI coding agents — finds hardcoded secrets, exposed .env files, git-history leaks and vulnerable dependencies (OSV), entirely on your machine. Ask your agent "is this safe to ship?" and get a Launch Readiness score with a fix for every finding.
Enables security scanning of code projects to identify common vulnerabilities like XSS, injections, SSRF, and path traversal issues. Provides local, offline scanning with severity-grouped results and actionable fix suggestions for improving code security.
Enables AI coding tools to scan projects for security vulnerabilities, hardcoded secrets, injection flaws, and privacy violations with 699 rules and 76 MCP tools, all running locally with zero telemetry.
Local-first AI compliance scanner via Model Context Protocol, scanning codebases for violations of DPDPA 2023, RBI FREE-AI, SEBI AI/ML, and the EU AI Act.
Enables AI-powered code safety analysis including risk detection, secret scanning, dependency checking, and code snapshot management. Works offline for basic features with optional cloud integration for advanced ML analysis and team collaboration.
Enables security auditing, penetration testing, and compliance validation with tools like Semgrep, Trivy, Gitleaks, and OWASP ZAP. Features strict project boundary enforcement and supports OWASP, CIS, and NIST compliance frameworks.
