Open-source AI security agent: SAST, DAST, and policy-as-code over MCP.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ or use 1-click editor setup below.
๐ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
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AI code-review assistant for application security.
Open-source. Reads your code, flags likely security issues, explains its reasoning, suggests fixes.
Quick Start โข How It Works โข Commands โข Hunt Mode โข Variant Analysis โข Integrations โข Contributing โข Vision โข Roadmap
mythos-agent reviews your code the way a reviewer on a security-focused team would. It walks through likely issue patterns, checks for variants of known CVEs, ranks findings by confidence, and suggests fixes you can accept or reject. See VISION.md for the full framing.
For new contributors: the active 6-month working plan is in the pinned issue
[Roadmap] mythos-agent H1 2026 Goals. Look for ๐ markers to spot items where help is wanted. New here? See CONTRIBUTING.md forgood-first-issueguidance.For security teams and EU CRA-compliant downstream manufacturers: see SECURITY.md for our vulnerability disclosure SLAs, docs/security/cra-stance.md for our EU CRA role declaration, docs/security/threat-model.md for our public threat model, and RELEASES.md for our versioning, LTS, and EOL policy. OpenSSF Best Practices Badge (Passing) submission targeted June 2026; releases are signed via Sigstore and ship with CycloneDX SBOMs for downstream Manufacturer compliance.
mythos-agent combines three things no other open-source tool does together:
Instead of matching known patterns, the AI reasons about what COULD go wrong, generating hypotheses like "this transaction doesn't lock the row, potential race condition" or "this auth check uses string comparison, potential timing attack."
Given a known CVE, mythos-agent finds structurally similar but syntactically different code in your codebase. Same root cause, different location. This is how Google's Big Sleep found 20 real zero-days.
Every finding goes through a confidence pipeline:
Only findings that survive multiple stages are reported as "confirmed."
| Command | Description |
|---|---|
hunt [path] | Full autonomous multi-agent scan (Recon โ Hypothesize โ Analyze โ Exploit) |
scan [path] | Standard scan (patterns + secrets + deps + IaC + AI) |
variants [cve-id] | Find variants of known CVEs in your codebase |
fix [path] | AI-generated patches with --apply |
ask [question] | Natural language security queries |
taint [path] | AI data flow / taint analysis |
watch | Continuous monitoring that scans on file save |
dashboard | Local web UI with charts and findings table |
report [path] | Export as terminal / JSON / HTML / SARIF |
policy | Policy-as-code with SOC2/HIPAA/PCI/OWASP compliance |
rules | Community rule pack registry (search/install/publish) |
tools | Check which external security tools are installed |
init | Setup wizard (Anthropic, OpenAI, Ollama, LM Studio) |
mythos-agent hunt runs the full multi-agent pipeline:
Find code in your project that has the same root cause as known CVEs:
The variant analyzer extracts the root cause pattern from the CVE (not the surface syntax) and searches your codebase for structurally similar code.
The Default scanners run on every mythos-agent scan. Experimental scanners are implemented + unit-tested classes that ship in the tarball but are not yet reachable from any CLI, HTTP, MCP, or agent entry point. They are tracked by KNOWN_EXPERIMENTAL in the wiring-invariant test.
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