MCPInstall

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 when comparing code between commits or tags, analyzing structural evolution, detecting attack surface growth, reviewing what changed between audit snapshots, or finding security-relevant changes that text diffs miss.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/trailofbits/skills --skill graph-evolution
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads graph-evolution automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

Security audits

Independent scans of the skill's instructions and bundled files.

Gen Agent Trust Hub PassSAFE ·The skill facilitates structural code analysis between source code snapshots using the Trailmark tool. It is generally safe but processes untrusted code, which is an inherent surface for indirect prompt injection. The skill includes human review checkpoints to manage this risk.
Socket PassNo alerts
Snyk PassLOW ·Risk: LOW · No issues
ZeroLeaks PassNONE ·Score: 93/100 · 2 sections analyzed

SKILL.md

The instructions your agent reads when the skill is triggered.

Graph Evolution

Builds Trailmark code graphs at two source snapshots and computes a structural diff. Surfaces security-relevant changes that text-level diffs miss: new attack paths, complexity shifts, blast radius growth, taint propagation changes, and privilege boundary modifications.

When to Use

  • Comparing two git refs to understand what structurally changed
  • Auditing a range of commits for security-relevant evolution
  • Detecting new attack paths created by code changes
  • Finding functions whose blast radius or complexity grew silently
  • Identifying taint propagation changes across refactors
  • Pre-release structural comparison (tag-to-tag or branch-to-branch)

When NOT to Use

  • Line-level code review (use differential-review for text-diff analysis)
  • Single-snapshot analysis (use the trailmark skill directly)
  • Diagram generation from a single snapshot (use the diagramming-code skill)
  • Mutation testing triage (use the genotoxic skill)

Rationalizations to Reject

RationalizationWhy It's WrongRequired Action
"We just need the structural diff, skip pre-analysis"Without pre-analysis, you miss taint changes, blast radius growth, and privilege boundary shiftsRun engine.preanalysis() on both snapshots
"Text diff covers what changed"Text diffs miss new attack paths, transitive complexity shifts, and subgraph membership changesUse structural diff to complement text diff
"Only added nodes matter"Removed security functions and shifted privilege boundaries are equally dangerousReview removals and modifications, not just additions
"Low-severity structural changes can be ignored"INFO-level changes (dead code removal) can mask removed security checksClassify every change, review removals for replaced functionality
"One snapshot's graph is enough for comparison"Single-snapshot analysis can't detect evolution — you need both before and afterAlways build and export both graphs
"Tool isn't installed, I'll compare manually"Manual comparison misses what graph analysis catchesInstall trailmark first
"The diff came back empty, so nothing changed structurally"trailmark diff defaults --language to python and exits 0 with empty arrays on any other target, so an empty diff reads identically whether the code is unchanged or the language was wrongPass --language explicitly and re-run before concluding no change

Prerequisites

trailmark must be installed. If uv run trailmark fails, run:

uv tool install trailmark
# Python snippets: uv run --with trailmark python -   (a tool env is not importable)

DO NOT fall back to "manual comparison" or reading source files as a substitute for running trailmark. The tool must be installed and used programmatically. If installation fails, report the error.


Quick Start

# Compare two git refs (e.g., tags, branches, commits)
# 1. Build graphs at each snapshot
# 2. Run pre-analysis on both
# 3. Compute structural diff
# 4. Generate report

# Step-by-step: see Workflow below

Decision Tree

├─ Need to understand what each metric means?
│  └─ Read: references/evolution-metrics.md
│
├─ Need the report output format?
│  └─ Read: references/report-format.md
│
├─ Already have two graph JSON exports?
│  └─ Jump to Phase 3 (run native diff + graph_diff.py)
│
└─ Starting from two git refs?
   └─ Start at Phase 1

Workflow

Graph Evolution Progress:
- [ ] Phase 1: Create snapshots (git worktrees)
- [ ] Phase 2: Build graphs + pre-analysis on both snapshots
- [ ] Phase 3: Compute structural diff
- [ ] Phase 4: Interpret diff and generate report
- [ ] Phase 5: Clean up worktrees

Phase 1: Create Snapshots

Use git worktrees to get clean copies of each ref without disturbing the working tree.

# Create temp directories for worktrees
BEFORE_DIR=$(mktemp -d)
AFTER_DIR=$(mktemp -d)

# Create worktrees (run from repo root)
git worktree add "$BEFORE_DIR" {before_ref}
git worktree add "$AFTER_DIR" {after_ref}

If comparing two directories instead of git refs, skip this phase and use the directory paths directly in Phase 2.

Phase 2: Build Graphs and Run Pre-Analysis

Build Trailmark graphs for both snapshots and run pre-analysis on each. Pre-analysis computes blast radius, taint propagation, privilege boundaries, and entrypoint enumeration.

from trailmark.query.api import QueryEngine

def build_and_export(target_dir, output_path, language="auto"):
    """Build graph, run pre-analysis, export JSON."""
    engine = QueryEngine.from_directory(target_dir, language=language)
    engine.preanalysis()
    json_str = engine.to_json()
    with open(output_path, "w") as f:
        f.write(json_str)
    return engine.summary()

import tempfile, os
work_dir = tempfile.mkdtemp(prefix="trailmark_evolution_")
before_json = os.path.join(work_dir, "before_graph.json")
after_json = os.path.join(work_dir, "after_graph.json")

before_summary = build_and_export(
    "{before_dir}", before_json
)
after_summary = build_and_export(
    "{after_dir}", after_json
)

Verify both graphs built successfully by checking the summary output. If either fails, rerun with an explicit language or comma-separated list instead of auto.

Phase 3: Compute Structural Diff

Run both:

  1. Trailmark's native structural diff for nodes, edges, and entrypoints
  2. The plugin's graph_diff.py helper for subgraph membership changes

Use the same work_dir from Phase 2, and pass the same --language value Phase 2 built with. trailmark diff defaults that flag to python, so on any other target the default exits 0 and writes empty arrays rather than reporting a mismatch.

trailmark diff --json --language auto "{before_dir}" "{after_dir}" > "{work_dir}/trailmark_diff.json" || \
  uv run trailmark diff --json --language auto "{before_dir}" "{after_dir}" > "{work_dir}/trailmark_diff.json"

uv run {baseDir}/scripts/graph_diff.py \
    --before "{before_json}" \
    --after "{after_json}" > "{work_dir}/subgraph_diff.json"

If Phase 2 needed an explicit language or a comma-separated list instead of auto, use that same value here.

If either diff command fails or writes an empty JSON file, stop and report the error instead of continuing to Phase 4.

A trailmark_diff.json whose nodes, edges, and entrypoints arrays are all empty means either nothing changed structurally or both snapshots parsed to (near-)empty graphs. Decide which using Phase 2's graph summaries: if either snapshot's node count is zero or implausibly small for the target, the parse missed the code — name the language set explicitly (rust, solidity, python,rust) and re-run. Healthy node counts on both snapshots plus an empty diff is genuine structural stability.

The native Trailmark diff contains:

KeyContents
summary_deltaChanges in node/edge/entrypoint counts
nodes.addedNew functions, classes, methods
nodes.removedDeleted functions, classes, methods
nodes.modifiedFunctions with changed CC, params, line span
edges.addedNew call/inheritance/import relationships
edges.removedDeleted relationships
entrypointsAdded, removed, and modified entrypoints

The subgraph diff contains:

KeyContents
subgraphsPer-subgraph membership changes (tainted, high_blast_radius, etc.)

Phase 4: Interpret Diff and Generate Report

Read both diff JSON files and generate a security-focused markdown report. See references/report-format.md for the full template.

Interpretation priorities (highest to lowest):

  1. New tainted paths — nodes entering the tainted subgraph, especially if they also appear in added edges targeting sensitive functions
  2. Privilege boundary changes — new or removed trust transitions from the native entrypoint/edge diff plus the subgraph diff
  3. Attack surface growth — new entrypoints, especially untrusted_external, from trailmark_diff.json
  4. Blast radius increases — nodes entering high_blast_radius
  5. Complexity spikes — CC increases > 3 on tainted or entrypoint-reachable nodes
  6. Structural additions — new nodes and edges (review needed)
  7. Structural removals — verify removed security functions were replaced

Cross-reference structural changes with git diff {before_ref}..{after_ref} to add source-level context to findings.

Severity classification:

SeverityStructural Signal
CRITICALNew tainted path to sensitive function, removed auth boundary
HIGHNew entrypoint + high blast radius, large CC increase on tainted node
MEDIUMNew trust-boundary-crossing edges, moderate CC increase
LOWAdded nodes without entrypoint reachability
INFODead code removal, complexity reductions

For detailed metric definitions, see references/evolution-metrics.md.

Phase 5: Clean Up

Remove git worktrees after the report is written:

git worktree remove "{before_dir}"
git worktree remove "{after_dir}"

Diff Reference

trailmark diff --json --language auto BEFORE AFTER
uv run {baseDir}/scripts/graph_diff.py [OPTIONS]

trailmark diff --language defaults to python. On a target in any other language that default still exits 0, emitting well-formed JSON with empty nodes, edges, and entrypoints arrays, so always pass the flag: auto detects and merges every supported language found under the target, and a single name (rust, solidity) or comma-separated list (python,rust) pins an explicit set. auto fails loudly with No supported languages detected under <path> when a snapshot holds nothing it can parse, which is the outcome you want. Confirm the language first; only then can an empty diff count as evidence that nothing changed.

Use trailmark diff for:

  • Node/edge changes
  • Added/removed/modified entrypoints
  • Human-readable structural diff reports

Use graph_diff.py for:

  • Subgraph membership changes derived from engine.preanalysis()
  • tainted, high_blast_radius, privilege_boundary, and related sets
ArgumentDefaultDescription
--beforerequiredPath to the "before" graph JSON
--afterrequiredPath to the "after" graph JSON
--indent2JSON output indentation

graph_diff.py input format: Trailmark JSON exports from engine.to_json(). graph_diff.py output: JSON structural diff for nodes, edges, and subgraphs.


Quality Checklist

Before delivering the report:

  • Both graphs built successfully (check summaries)
  • Pre-analysis ran on both snapshots
  • Native Trailmark diff computed (trailmark_diff.json); if it is empty, both snapshots' Phase 2 node counts were non-zero, so empty means stable
  • Subgraph diff computed and non-empty (subgraph_diff.json)
  • All subgraph changes interpreted (tainted, blast radius, etc.)
  • Critical findings include evidence (node IDs, edge diffs)
  • Severity levels assigned to all findings
  • Source-level context added via git diff cross-reference
  • Worktrees cleaned up (or temp dirs removed)
  • Report written to GRAPH_EVOLUTION_*.md

Integration

trailmark skill: Phase 2 uses the trailmark API for graph building and pre-analysis. All trailmark query patterns work on either snapshot's engine.

differential-review skill: Use graph-evolution for structural analysis, differential-review for line-level code review. The two are complementary — graph-evolution finds attack paths that text diffs miss, while differential-review provides git blame context and micro-adversarial analysis.

trailmark-review-gate skill: Use trailmark-review-gate after graph-evolution when a branch, pull request, fix commit, or release diff needs a PASS/WARN/FAIL/UNKNOWN structural review packet. The gate applies deterministic review rules to graph-evolution output; it does not replace human review.

genotoxic skill: If graph-evolution reveals new high-CC tainted nodes, feed them to genotoxic for mutation testing triage.

diagramming-code skill: Generate before/after diagrams to visualize structural changes. Use call-graph or data-flow diagrams focused on changed nodes.


Supporting Documentation

  • references/evolution-metrics.md — What each structural metric means and why it matters for security
  • references/report-format.md — Report template, severity classification, and example findings

FAQ

What does the graph-evolution skill do?

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 when comparing code between commits or tags, analyzing structural evolution, detecting attack surface growth, reviewing what changed between audit snapshots, or finding security-relevant changes that text diffs miss.

How do I install graph-evolution?

Run npx skills add https://github.com/trailofbits/skills --skill graph-evolution in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/graph-evolution/ (personal) or .claude/skills/graph-evolution/ (project).

Which AI agents can use graph-evolution?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is graph-evolution safe to install?

Security partners have reviewed it: Gen Agent Trust Hub passed; Socket passed; Snyk passed; ZeroLeaks passed. As with any skill, read the SKILL.md and bundled scripts before installing.

Who maintains graph-evolution?

It is published by trailofbits in trailofbits/skills. It has 3,917 recorded installs.

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