The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Mythos Agent listing page.
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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 • How It Works • Commands • Hunt Mode • Variant Analysis • Integrations • Contributing • Vision • 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 🙋 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 → Hypothesize → Analyze → 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.
| Category | What it finds | Rules | Status |
|---|---|---|---|
| Code patterns | SQLi, XSS, command injection, eval, SSRF, etc. | 25+ | Default |
| Framework rules | React, Next.js, Express, Django, Flask, Spring, Go | 27 | Default |
| Secrets | AWS, GitHub, Stripe, API keys, DB URLs, private keys + entropy | 22 | Default |
| Dependencies (SCA) | Known CVEs via OSV API (10 lockfile formats) | OSV | Default |
| IaC | Docker, Terraform, Kubernetes misconfigurations | 13 | Default |
| AI/LLM Security | Prompt injection, unsafe eval of AI output, cost attacks | 13 | Default |
| API Security | OWASP API Top 10: BOLA, mass assignment, broken auth | 12 | Default |
| Cloud Misconfig | AWS/Azure/GCP: public storage, wildcard IAM, open firewalls | 14 | Default |
| Security Headers | CSP, HSTS, X-Frame-Options, Referrer-Policy | 8 | Default |
| JWT | Algorithm, expiry, storage, revocation, audience | 9 | Default |
| Session | Fixation, expiry, cookie flags, localStorage tokens | 7 | Default |
| Business Logic | Negative amounts, coupon reuse, inventory races, role escalation | 6 | Default |
| Crypto Audit | Weak hashes, ECB mode, hardcoded keys, deprecated TLS | 11 | Default |
| Privacy/GDPR | PII handling, consent, data retention (GDPR article mapping) | 9 | Default |
| Race Conditions | TOCTOU, non-atomic ops, double-spend, missing transactions | 7 | Default |
| ReDoS | Catastrophic backtracking in regex (nested quantifiers, overlapping alternatives) | — | Default |
| Supply Chain | Typosquatting, dependency confusion, dangerous install scripts | 12 | Experimental |
| Zero Trust | Service trust, mTLS, network segmentation, IP-based auth | 8 | Experimental |
| GraphQL | Introspection, depth limit, field auth, batching | 8 | Experimental |
| WebSocket | Auth, origin check, message validation, broadcast XSS | 7 | Experimental |
| CORS | Origin reflection, credentials handling, substring bypass | 7 | Experimental |
| OAuth/OIDC | Missing state, no PKCE, implicit flow, client secret exposure | 7 | Experimental |
| SSTI | Jinja2, EJS, Handlebars, Pug, Nunjucks, Twig, Go templates | 7 | Experimental |
SQL injection deep, XSS deep, NoSQL, command injection, deserialization, path traversal, open redirect, XXE, input validation, clickjacking, DNS rebinding, subdomain enumeration, dep confusion, environment variables, logging, error handling, cache, email, upload, memory safety, permissions.
Each exists as a class under src/scanner/ and has unit tests in src/scanner/__tests__/coverage-scanners.test.ts / new-scanners.test.ts, but is not invoked by any CLI command, HTTP API route, MCP handler, or agent pipeline. See KNOWN_EXPERIMENTAL in the wiring-invariant test for each scanner's deferral reason. Wiring one up follows the pattern of the HeadersScanner / JwtScanner / SessionScanner / BusinessLogicScanner commits on main.
Beyond the scanners above, mythos-agent ships complementary analyses (not counted in the scanner totals): call-graph + taint engine, DAST smart fuzzer, AI hypothesis agent, variant analysis, and git-history mining.
External tool integrations: Semgrep (30+ languages), Gitleaks (100+ patterns), Trivy (SCA + containers), Checkov (1000+ IaC policies), Nuclei (9000+ DAST templates)
| Platform | What |
|---|---|
| VS Code | Extension with inline diagnostics + one-click AI fix |
| GitHub Action | Scan on push/PR + SARIF upload to Code Scanning |
| PR Review Bot | Inline comments on vulnerable lines in pull requests |
| Dashboard | Local web UI at mythos-agent dashboard |
| SARIF | GitHub Code Scanning, VS Code, any SARIF tool |
| Policy Engine | SOC2, HIPAA, PCI-DSS, OWASP compliance mapping |
| Tier | Providers | Status |
|---|---|---|
| 1 — Primary | Anthropic (Claude Sonnet / Opus / Haiku) | Fully tested. Published catch-rate numbers in docs/benchmarks/external-scores.md are produced with this tier. |
| 2 — Compatible (proxy today, native in stage 2) | Anything OpenAI-compatible — OpenAI, Qwen via DashScope/OpenRouter, Gemini, Mistral, vLLM, Ollama, LM Studio, Bedrock, etc. | Today: route through any Anthropic-compatible proxy (LiteLLM, OpenRouter, Vercel AI Gateway, Bedrock) by setting baseURL in .mythos.yml or ANTHROPIC_BASE_URL env. Native OpenAI SDK support lands in stage 2. |
| 3 — Local / community | Local Ollama / LM Studio / vLLM | Same code path as Tier 2; called out separately because privacy and cost-of-zero are the use case. Best-effort; agentic tool-use quality depends on local model size. |
Pattern scanning, secrets, deps, and IaC work without any API key.
See docs/multi-model.md for the full tier-system policy + the staged rollout (this README is the summary; that doc is the canonical reference).
| Feature | mythos-agent | Semgrep | Snyk | CodeQL | Nuclei |
|---|---|---|---|---|---|
| Pattern scanning | Yes | Best | Yes | Yes | Templates |
| Hypothesis scanning | Yes | No | No | No | No |
| Variant analysis | Yes | No | No | Partial | No |
| AI-guided fuzzing | Yes | No | No | No | Templates |
| PoC generation | Yes | No | No | No | No |
| AI deep analysis | Yes | No | Limited | No | No |
| Vuln chaining | Yes | No | No | No | No |
| AI auto-fix | Yes | No | Fix PRs | No | No |
| NL queries | Yes | No | No | No | No |
| Secrets | Yes | Yes | Yes | No | No |
| SCA | Yes | No | Best | No | No |
| IaC | Yes | No | Yes | No | Templates |
| DAST | Yes | No | No | No | Best |
| Open source | Yes | Partial | No | Yes | Yes |
This feature table is a capability comparison, not an accuracy claim. For reproducible, third-party-runnable accuracy numbers vs Semgrep CE / Snyk Code / CodeQL on OWASP Benchmark, CyberSecEval 3, Vul4J, and our CVE replay harness, see docs/benchmarks/external-scores.md.
See CONTRIBUTING.md for details.
MIT