attackmap 0.1.1

AI-assisted defensive security analyzer for codebases — scans a repository, models assets and controls, finds cross-cutting weaknesses, and generates an evidence-grounded review with MITRE ATT&CK mappings and detection-engineering hints.

AttackMap

AI-assisted defensive security analysis for codebases. AttackMap reads your repository, models its assets and defensive controls, finds cross-cutting weaknesses that single-file scanners miss, and produces an evidence-grounded security review with MITRE ATT&CK mappings and detection-engineering hints.

Built for AppSec engineers, SOC and detection-engineering teams, and engineering managers who need to triage an unfamiliar codebase.

Story over checklist. Asset-aware. Control-absence-aware. Evidence-grounded.

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Quickstart

Install with all bundled analyzers:

pip install "attackmap[all]"

Run a review on a repository:

attackmap analyze /path/to/repo --output reports

Optional: add an AI-narrated review using Claude. Either set an ANTHROPIC_API_KEY, or log in once with the Claude Code CLI to use your existing Pro/Max subscription:

attackmap analyze /path/to/repo --output reports --llm

Read reports/defensive-review.md (heuristic) and reports/defensive-review-llm.md (LLM-narrated) side by side.

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Install

From PyPI

pip install attackmap                  # core only
pip install "attackmap[llm]"           # add LLM narrative support
pip install "attackmap[all]"           # core + LLM + all 13 analyzer plugins

You can also install individual analyzer plugins on demand:

pip install attackmap-analyzer-python attackmap-analyzer-go

With Docker

docker run --rm -v "$PWD:/src" ghcr.io/mlaify/attackmap:latest analyze /src --output /src/reports

With Homebrew (macOS)

brew install mlaify/tap/attackmap

From source

git clone https://github.com/mlaify/AttackMap.git
cd AttackMap
pip install -e ".[llm]"

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What you get

Every attackmap analyze run writes:

File	What it is
architecture.md	High-level summary of the repository
attack-surface.md	Surfaces classified by category, exposure, and risk
defensive-review.md	Notable Observations, Asset Inventory, Defensive Controls, Strengths, Weaknesses, Detection Opportunities, Recommendations
defensive-review.json	Structured equivalent (schema v1.2.0)
review-context-pack.json	Structured evidence pack consumed by the LLM stage
attackmap-report.json	Everything bundled
defensive-review-llm.md (with --llm)	Claude-narrated review
defensive-review-llm.meta.json (with --llm)	Backend, model, token usage

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How it works

AttackMap is built as four layers, each grounded in the layer below.

1. Heuristic scanner + analyzer plugins. Language-aware extraction of routes, databases, external calls, auth signals, secrets, frameworks, and entrypoints. Every signal carries a file:line citation, an evidence-text snippet, and a confidence score. Plugins are auto-discovered through the attackmap.analyzers entry-point group.

2. Asset and control overlay. Identifies what's at risk (credentials, sessions, PII, payment records, internal secrets — with criticality tiers) and what protects it (authentication, authorization, input validation, rate limiting, CSRF, encryption, audit logging, RBAC, MFA), including detection of absent expected controls.

3. Cross-cutting insight engine. Connects findings into narratives — sensitive-asset reachability, shared-secret blast radius, defense gaps in attack chains, control-strength mismatches, asymmetric protection, audit gaps, trust-boundary violations, and more.

4. LLM narrative review. With --llm, Claude Opus generates a final review from the structured evidence pack. The model is forced to cite real surface/asset/control IDs, so it can't invent findings.

Layered on top: MITRE ATT&CK technique mappings on every insight and detection opportunities (Sigma/KQL/Splunk-style hints) for each weakness.

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Supported ecosystems

Thirteen official analyzer plugins, each distributable as a separate package:

Plugin	Coverage
attackmap-analyzer-python	Django, Starlette, AIOHTTP, Sanic, Litestar, DRF; SQLAlchemy/asyncpg/motor; passlib/PyJWT/authlib; httpx/aiohttp
attackmap-analyzer-rust	axum, actix-web, rocket; sqlx, diesel, sea-orm; jsonwebtoken, argon2; reqwest
attackmap-analyzer-go	net/http, chi, gin, echo, fiber, gorilla/mux; database/sql, gorm, pgx; golang-jwt; resty
attackmap-analyzer-java-spring	Java/Kotlin Spring Boot, JAX-RS, Ktor; Spring Data; Spring Security; jjwt
attackmap-analyzer-dotnet	ASP.NET Core minimal APIs and attribute routing, EF Core, Identity, JwtBearer
attackmap-analyzer-terraform	AWS, Azure, GCP resources; IAM wildcards; open SGs; secrets
attackmap-analyzer-c	libmicrohttpd, civetweb, mongoose; libcurl; OpenSSL/libsodium; sqlite3/libpq/mysql
attackmap-analyzer-cpp	Crow, Pistache, Drogon, cpprestsdk; libcurl/cpr; OpenSSL/Botan/libsodium; libpqxx/mongocxx
attackmap-analyzer-node-service	Node.js / TypeScript service ecosystems
attackmap-analyzer-atproto	AT Protocol (Bluesky) services
attackmap-analyzer-php-web / -php-laminas / -omeka-s	Generic PHP web, Laminas/Zend MVC, Omeka-S

pip install "attackmap[all]" installs every official plugin.

Building your own analyzer

The plugin contract is documented in code at attackmap.sdk; the developer cookbook with scaffolding, testing, and publishing instructions is in docs/external-analyzers.md.

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CLI reference

attackmap analyze <path>                 # run a review on a repository
attackmap analyze <path> --output dir    # write outputs to `dir/`
attackmap analyze <path> --module python --module rust   # only these analyzers
attackmap analyze <path> --llm           # add LLM narrative (auto-resolve auth)
attackmap analyze <path> --llm --llm-backend cli         # force Claude CLI
attackmap modules                        # list installed analyzers

--module is repeatable. Missing requested external analyzers can be auto-installed (when possible) from the mlaify GitHub organization.

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What AttackMap is not

• A runtime detector. AttackMap is static. The detection opportunities it emits are hints for your SIEM team — they are not deployable rules.
• A vulnerability scanner. AttackMap models architecture, assets, and controls. It does not match known-CVE patterns.
• Exhaustive. AttackMap is heuristic by design. Findings are confidence-tiered with explicit guardrails for stale signals.

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Documentation

• CHANGELOG.md — release notes
• CONTRIBUTING.md — development setup and PR process
• SECURITY.md — vulnerability disclosure
• AGENTS.md — agent-facing repo guide
• VISION.md — project direction
• GitHub wiki — deeper architecture and analyzer-contract references

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Contributing

Issues and pull requests are welcome. See CONTRIBUTING.md for setup, testing, and submission guidelines. By contributing you agree that your contributions will be MIT-licensed.

License

MIT. Copyright (c) 2026 Matthew Davis and AttackMap Contributors.