ATTACKMAP

Map findings to MITRE ATT&CK techniques + coverage heatmap

Part of the Cognis Neural Suite.

pip install cognis-attackmap
attackmap scan .            # → prioritized findings in seconds

Contents

• Why attackmap? · Features · Quick start · Example · Architecture · AI stack · How it compares · Integrations · Install anywhere · Related · Contributing

Why attackmap?

speak ATT&CK

attackmap is single-purpose, scriptable, and self-hostable: point it at a target, get prioritized results in the format your workflow already speaks (table · JSON · SARIF), gate CI on it, and let agents drive it over MCP.

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Features

• ✅ Lookup Technique
• ✅ Resolve Keywords
• ✅ Map Findings
• ✅ Coverage Heatmap
• ✅ Navigator Layer
• ✅ Parse Findings
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

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Quick start

pip install cognis-attackmap
attackmap --version
attackmap scan .                       # scan current project
attackmap scan . --format json         # machine-readable
attackmap scan . --fail-on high        # CI gate (non-zero exit)

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Example

$ attackmap scan .
  [HIGH    ] ATT-001  example finding             (./src/app.py)
  [MEDIUM  ] ATT-002  another signal              (./config.yaml)

  2 findings · risk score 5 · 38ms

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Architecture

flowchart LR
  A[Input: file / dir / API] --> B[Collectors]
  B --> C[Rules / Analyzers]
  C --> D[Scorer]
  D --> E{Reporters}
  E --> F[Table]
  E --> G[JSON / SARIF]
  E --> H[MCP tool -. drives .-> AI agents]

Loading

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Use it from any AI stack

attackmap is interoperable with every popular way of using AI:

• MCP server — attackmap mcp (Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet)
• OpenAI-compatible / JSON — pipe attackmap scan . --format json into any agent or LLM
• LangChain · CrewAI · AutoGen · LlamaIndex — wrap the CLI/JSON as a tool in one line
• CI / scripts — exit codes + SARIF for non-AI pipelines

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How it compares

	Cognis attackmap	ATT&CK Navigator
Self-hostable, no account	✅	varies
Single command, zero config	✅	⚠️
JSON + SARIF for CI	✅	varies
MCP-native (AI agents)	✅	❌
Polyglot ports (JS/Go/Rust)	✅	❌
Open license	✅ COCL	varies

Built in the spirit of ATT&CK Navigator, re-framed the Cognis way. Missing a credit? Open a PR.

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Integrations

Pipes into your stack: SARIF for code-scanning, JSON for anything, an MCP server (attackmap mcp) for AI agents, and a webhook forwarder for SIEM/Slack/Jira. See docs/INTEGRATIONS.md.

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Install — every way, every platform

pip install "git+https://github.com/cognis-digital/attackmap.git"    # pip (works today)
pipx install "git+https://github.com/cognis-digital/attackmap.git"   # isolated CLI
uv tool install "git+https://github.com/cognis-digital/attackmap.git" # uv
pip install cognis-attackmap                                          # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/attackmap:latest --help        # Docker
brew install cognis-digital/tap/attackmap                             # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/attackmap/main/install.sh | sh

Linux	macOS	Windows	Docker	Cloud
scripts/setup-linux.sh	scripts/setup-macos.sh	scripts/setup-windows.ps1	docker run ghcr.io/cognis-digital/attackmap	DEPLOY.md (AWS/Azure/GCP/k8s)

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Related Cognis tools

• portfan — Summarize and diff nmap XML into prioritized, attackable findings
• subhunt — Aggregate & dedupe subdomain enumeration from multiple sources
• dirsight — Analyze web content-discovery output (ffuf/gobuster) into ranked endpoints
• jwtinspect — Decode JWTs and lint for alg=none, weak secrets, and missing claims
• corsaudit — Detect permissive/misconfigured CORS from headers or a config
• headerscan — Grade HTTP security headers (CSP/HSTS/XFO) A-F from a response dump

Explore the suite → 🗂️ all 170+ tools · ⭐ awesome-cognis · 🔗 cognis-sources · 🤖 uncensored-fleet · 🧠 hermes

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Contributing

PRs, new rules, and demo scenarios are welcome under the collaboration-pull model — see CONTRIBUTING.md and SECURITY.md.

⭐ If attackmap saved you time, star it — it genuinely helps others find it.

License

Source-available under the Cognis Open Collaboration License (COCL) v1.0 — free for personal, internal-evaluation, research, and educational use; commercial / production use requires a license (licensing@cognis.digital). See LICENSE.

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_{Cognis Digital · one of 170+ tools in the Cognis Neural Suite · Making Tomorrow Better Today}