
Mythos Agent
io.github.mythos-agentPublished by GitHub account mythos-agentv4.0.1Updated Oct 27, 2026
Open-source AI security agent: SAST, DAST, and policy-as-code over MCP.
Overview
Open-source AI security code-review agent that scans a local codebase for vulnerabilities, secrets, dependency and IaC issues, and suggests fixes.
- What you can do
- Scan code for vulnerability patterns, secrets, dependency CVEs, IaC misconfigurations, API, JWT, crypto and privacy issues
- Run a multi-stage autonomous hunt that forms hypotheses, verifies findings and generates proof-of-concept exploits
- Find variants of known CVEs by root-cause pattern, and trace data flow with taint analysis
- Generate AI patches, answer natural-language security questions, and map findings to SOC2/HIPAA/PCI/OWASP policies
- Export reports as terminal, JSON, HTML or SARIF, and serve a local dashboard
- Watch files for changes and check which external security tools are installed
- When to use it
- Useful when you want an assistant to review a local repository for security problems, triage findings by confidence, or check whether a known CVE pattern appears elsewhere in the code. Suited to security-focused code review before release or during pull-request work.
- Requirements
- Runs as a local npm package (npx mythos-agent) on a desktop machine. Pattern, secrets, dependency and IaC scanning work without an API key; the full autonomous hunt and AI features need a configured model provider (Anthropic, or an OpenAI-compatible or local endpoint via configuration or the ANTHROPIC_BASE_URL environment variable). Optional external tools such as Semgrep, Gitleaks, Trivy, Checkov and Nuclei add coverage.
Installation
In SourceWeft
- Open Mythos Agent in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
English · 简体中文
[mythos-agent — Cerby the guard puppy]
[mythos-agent — 10-second security check demo]
mythos-agent
AI code-review assistant for application security.
Open-source. Reads your code, flags likely security issues, explains its reasoning, suggests fixes.
[CI] [npm] [License] [Discord] [Node] [Wired scanners] [Experimental scanners] [Rules]
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.
Quick Start
How It Works
mythos-agent combines three things no other open-source tool does together:
1. Hypothesis-Driven Scanning
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."
2. Variant Analysis (Big Sleep technique)
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.
3. Multi-Stage Verification
Every finding goes through a confidence pipeline:
- Pattern scan → candidate
- AI hypothesis → theoretical risk confirmed
- Smart fuzzer → dynamically tested
- PoC generator → concrete exploit proves it's real
Only findings that survive multiple stages are reported as "confirmed."
Commands
Hunt Mode
mythos-agent hunt runs the full multi-agent pipeline:
Variant Analysis
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.
Scanners (15 wired + 28 experimental, 329+ rules)
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.
Additional experimental scanners (21 more, not yet wired into default scan)
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)
Integrations
AI Providers
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).
Comparison
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.
Contributing
See CONTRIBUTING.md for details.
Architecture
License
MIT
Source: README.md at commit a14abd1
Tools
0Version history
1- v4.0.1LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts