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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

Install / Use

npx skills add trailofbits/skills --skill graph-evolution

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

96/100

Category

Security

Supported Platforms

Universal

Our assessment of graph-evolution

graph-evolution scores 96/100 on our quality scale, 143rd of 774 Security skills we index (top 19%).

Its SKILL.md is 13 KB long, well organised into 26 sections with 9 code examples: a thorough specification that gives an agent plenty to work with.

With 7,225 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
16/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 4 days ago, so graph-evolution is actively maintained.
  • It is released under the CC-BY-SA-4.0 license; check its terms before commercial use.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-09-28. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

graph-evolution compared with similar skills

All 4 of these similar skills score higher than graph-evolution; compare them before choosing.

SkillScoreStarsUpdatedFormat
graph-evolution (this skill)by trailofbits967.2k4d agoSKILL.md
Agent-Reachby Panniantong10085.8k12d agoCLAUDE.md
algorithmic-artby anthropics100177.9k5d agoSKILL.md
pptxby anthropics100177.9k5d agoSKILL.md
designby nextlevelbuilder100130.2k6d agoSKILL.md

Frequently asked questions

How do I install graph-evolution?
Run npx skills add trailofbits/skills --skill graph-evolution. The install tabs above show the steps for each supported agent.
Which AI agents does graph-evolution work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is graph-evolution safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is CC-BY-SA-4.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is graph-evolution still maintained?
The repository was last updated 4 days ago, so graph-evolution is actively maintained.

name: graph-evolution description: > 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.

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

| Rationalization | Why It's Wrong | Required Action | |-----------------|----------------|-----------------| | "We just need the structural diff, skip pre-analysis" | Without pre-analysis, you miss taint changes, blast radius growth, and privilege boundary shifts | Run engine.preanalysis() on both snapshots | | "Text diff covers what changed" | Text diffs miss new attack paths, transitive complexity shifts, and subgraph membership changes | Use structural diff to complement text diff | | "Only added nodes matter" | Removed security functions and shifted privilege boundaries are equally dangerous | Review removals and modifications, not just additions | | "Low-severity structural changes can be ignored" | INFO-level changes (dead code removal) can mask removed security checks | Classify 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 after | Always build and export both graphs | | "Tool isn't installed, I'll compare manually" | Manual comparison misses what graph analysis catches | Install 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 wrong | Pass --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:

| Key | Contents | |-----|----------| | summary_delta | Changes in node/edge/entrypoint counts | | nodes.added | New functions, classes, methods | | nodes.removed | Deleted functions, classes, methods | | nodes.modified | Functions with changed CC, params, line span | | edges.added | New call/inheritance/import relationships | | edges.removed | Deleted relationships | | entrypoints | Added, removed, and modified entrypoints |

The subgraph diff contains:

| Key | Contents | |-----|----------| | subgraphs | Per-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:

| Severity | Structural Signal | |----------|------------------| | CRITICAL | New tainted path to sensitive function, removed auth boundary | | HIGH | New entrypoint + high blast radius, large CC increase on tainted node | | MEDIUM | New trust-boundary-crossing edges, moderate CC increase | | LOW | Added nodes without entrypoint reachability | | INFO | Dead 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

| Argument | Default | Description | |----------|---------|-------------| | --before | required | Path to the "before" graph JSON | | --after | required | Path to the "after" graph JSON | | --indent | 2 | JSON 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

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars7.2k
CategorySecurity
Updated4d ago
Forks615

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions