agentic-actions-audito…
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI,…
Runs full Trailmark structural analysis by building a graph, running `preanalysis()`, and reporting hotspots, taint, blast radius, privilege boundaries, attack surface, and version-gated Trailmark 0.4+/0.5+ data such as proxy counts, subgraph edges, type/reference summaries, and
Claude Code
$ npx -y skills add trailofbits/skills --skill trailmark-structural --agent claude-code
Codex
$ npx skills add trailofbits/skills --skill trailmark-structural -a codex -y
Cursor
$ npx skills add trailofbits/skills --skill trailmark-structural -a cursor -y
Gemini CLI
$ npx skills add trailofbits/skills --skill trailmark-structural -a gemini-cli -y
GitHub Copilot
$ npx skills add trailofbits/skills --skill trailmark-structural -a github-copilot -y
OpenCode
$ npx skills add trailofbits/skills --skill trailmark-structural -a opencode -y
Windsurf
$ npx skills add trailofbits/skills --skill trailmark-structural -a windsurf -y
name: trailmark-structural description: "Runs full Trailmark structural analysis by building a graph, running `preanalysis()`, and reporting hotspots, taint, blast radius, privilege boundaries, attack surface, and version-gated Trailmark 0.4+/0.5+ data such as proxy counts, subgraph edges, type/reference summaries, and entrypoint attributes. Use when vivisect needs detailed structural data for a target. Triggers: structural analysis, blast radius, taint analysis, complexity hotspots, proxy nodes, type references." allowed-tools: Bash Read Grep Glob
Builds a Trailmark graph and runs `engine.preanalysis()` to compute all four pre-analysis passes. The core workflow is v0.2-safe; v0.4-only details are included only after checking method availability, and newer builds enrich the same output (0.5.0+ adds an `attributes` key to attack-surface entries and `proxy.external:*` nodes from `.trailmark/links.toml`) without any workflow change.
summaries when Trailmark 0.4.0+ is installed
| Rationalization | Why It's Wrong | Required Action | |-----------------|----------------|-----------------| | "Summary analysis is enough" | Summary skips taint, blast radius, and privilege boundary data | Run full structural analysis when detailed data is needed | | "One pass is sufficient" | Passes cross-reference each other — taint without blast radius misses critical nodes | Run all four passes | | "Tool isn't installed, I'll analyze manually" | Manual analysis misses what tooling catches | Report "trailmark is not installed" and return | | "Empty pass output means the pass failed" | Some passes produce no data for some codebases (e.g., no privilege boundaries) | Return full output regardless | | "A v0.4 field is always present" | Users may still have Trailmark 0.2.x installed | Probe with `hasattr()` before querying v0.4-only methods |
The target directory is passed via the `args` parameter.
**Step 1: Check that trailmark is available.**
trailmark analyze --help 2>/dev/null || \ uv run trailmark analyze --help 2>/dev/null
If neither command works, report "trailmark is not installed" and return. Do NOT run `pip install`, `uv pip install`, `git clone`, or any install command. The user must install trailmark themselves.
Optionally record the version:
trailmark --version 2>/dev/null || uv run trailmark --version 2>/dev/null || true
Do not fail if this command is missing; use API feature probes below.
**Step 2: Detect languages with Trailmark's parse API.**
python3 - "{args}" <<'PY'
import json
import sys
try:
from trailmark.parse import detect_languages # canonical location since 0.3.x
except ModuleNotFoundError:
# v0.2.x predates trailmark.parse; the same function lives in query.api
from trailmark.query.api import detect_languages
print(json.dumps(detect_languages(sys.argv[1])))
PYIf the import fails, rerun the same snippet with `uv run --with trailmark python - "{args}"`. If the result is `[]`, report "Trailmark found no supported languages under target" and return.
**Step 3: Run the full structural analysis via `QueryEngine`.**
Run this snippet with `python3`. If the import fails, rerun the same snippet under `uv run --with trailmark python - "{args}"`.
python3 - "{args}" <<'PY'
import json
import sys
try:
from trailmark.parse import detect_languages # canonical location since 0.3.x
except ModuleNotFoundError:
# v0.2.x predates trailmark.parse; the same function lives in query.api
from trailmark.query.api import detect_languages
from trailmark.query.api import QueryEngine
target = sys.argv[1]
languages = detect_languages(target)
engine = QueryEngine.from_directory(target, language="auto")
preanalysis = engine.preanalysis()
def summarize_subgraph(name: str, limit: int = 25) -> dict[str, object]:
nodes = engine.subgraph(name)
summary = {
"count": len(nodes),
"sample_ids": [node["id"] for node in nodes[:limit]],
}
if hasattr(engine, "subgraph_edges"):
summary["edge_count"] = len(engine.subgraph_edges(name))
return summary
graph = json.loads(engine.to_json())
nodes = graph.get("nodes", {})
proxy_nodes = [
node_id for node_id, node in nodes.items()
if node.get("kind") == "proxy" or node.get("origin") == "proxy"
]
payload = {
"languages": languages,
"summary": engine.summary(),
"preanalysis": preanalysis,
"attack_surface": engine.attack_surface()[:25],
"hotspots": engine.complexity_hotspots(10)[:25],
"proxy_nodes": proxy_nodes[:25],
"subgraphs": {
name: summarize_subgraph(name)
for name in engine.subgraph_names()
},
}
if hasattr(engine, "type_references"):
payload["type_reference_samples"] = {
node_id: engine.type_references(node_id)[:10]
for node_id in list(nodes)[:25]
}
print(json.dumps(payload, indent=2))
PY**Step 4: Verify the output.**
The output should include:
0.5.0+ may include `proxy.external:*` entries declared in `.trailmark/links.toml`)
On Trailmark 0.5.0+, `attack_surface` entries may carry an `attributes` object (e.g. `solidity_visibility`, `solidity_overridden_by`). P
Trail of Bits skills and plugins for AI-assisted security analysis, testing, and development. Install this marketplace in Claude Code or Codex, or import it into your ChatGPT workspace marketplace.
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