claude

trailmark

Builds multi-language source code graphs for security analysis: call graphs, attack surface mapping, blast radius, taint propagation, complexity hotspots, and entry point enumeration. Generates Mermaid diagrams (call graphs, class hierarchies, dependency maps, heatmaps). Compares code graph snapshots for structural diff and evolution analysis. Runs graph-informed mutation testing triage (genotoxic). Generates mutation-driven test vectors (vector-forge). Extracts crypto protocol message flows and converts Mermaid diagrams to ProVerif models. Projects SARIF and weAudit findings onto code graphs. Use when analyzing call paths, mapping attack surface, visualizing code architecture, triaging survived mutants, generating cryptographic test vectors, diagramming crypto protocols, formally verifying protocols, or augmenting audits with static analysis findings.

0 on GitHubby Scott Arciszewskiv0.8.2CC-BY-SA-4.0updated 4 months ago
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Plugin trailmark from marketplace trailofbits in RUSHYOP/mirror-trailofbits-skills. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (10)

  • audit-augmentation

    Augments Trailmark code graphs with external audit findings from SARIF static analysis results and weAudit annotation files. Maps findings to graph nodes by file and line overlap, creates severity-based subgraphs, and enables cross-referencing findings with pre-analysis data (blast radius, taint, et

  • crypto-protocol-diagram

    Extracts protocol message flow from source code, RFCs, academic papers, pseudocode, informal prose, ProVerif (.pv), or Tamarin (.spthy) models and generates Mermaid sequenceDiagrams with cryptographic annotations. Use when diagramming a crypto protocol, visualizing a handshake or key exchange flow,

  • diagramming-code

    Generates Mermaid diagrams from Trailmark code graphs. Produces call graphs, class hierarchies, module dependency maps, containment diagrams, complexity heatmaps, and attack surface data flow visualizations. Use when visualizing code architecture, drawing call graphs, generating class diagrams, crea

  • genotoxic

    Graph-informed mutation testing triage. Parses codebases with Trailmark, runs mutation testing and necessist, then uses survived mutants, unnecessary test statements, and call graph data to identify false positives, missing test coverage, and fuzzing targets. Use when triaging survived mutants, anal

  • graph-evolution

    Compares Trailmark code graphs at two source code snapshots (git commits, tags, or directories) to surface security-relevant structural changes. Detects new attack paths, complexity shifts, blast radius growth, taint propagation changes, and privilege boundary modifications that text diffs miss. Use

  • mermaid-to-proverif

    Translates Mermaid sequenceDiagrams describing cryptographic protocols into ProVerif formal verification models (.pv files). Use when generating a ProVerif model, formally verifying a protocol, converting a Mermaid diagram to ProVerif, verifying protocol security properties (secrecy, authentication,

  • trailmark-structural

    Runs full Trailmark structural analysis on Trailmark 0.2.x by building a graph, running `preanalysis()`, and reporting hotspots, taint, blast radius, privilege boundaries, and attack surface. Use when vivisect needs detailed structural data for a target. Triggers: structural analysis, blast radius,

  • trailmark-summary

    Runs a Trailmark summary analysis on a codebase. Returns auto-detected languages, entry point count, and dependency list. Use when vivisect or galvanize needs a quick structural overview. Triggers: trailmark summary, code summary, structural overview.

  • trailmark

    Builds and queries multi-language source code graphs for security analysis. Includes pre-analysis passes for blast radius, taint propagation, privilege boundaries, and entry point enumeration. Use when analyzing call paths, mapping attack surface, finding complexity hotspots, enumerating entry point

  • vector-forge

    Mutation-driven test vector generation. Finds implementations of a cryptographic algorithm or protocol, runs mutation testing to identify escaped mutants, then generates new test vectors that deliberately exercise the uncovered code paths. Compares before/after mutation kill rates to prove vector ef

View source on GitHub

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