Audit Findings Graph Overlay

What it does

When your agent uses it

• Importing Semgrep or CodeQL SARIF output into a code graph
• Overlaying a human auditor's weAudit annotations on the call graph
• Finding which functions have high-severity findings and a wide blast radius
• Visualizing audit coverage alongside code structure

Example prompts

• “Import results.sarif from our Semgrep run into the Trailmark graph and list the functions with error-level findings.”
• “Overlay the weAudit file from the audit onto the graph and tell me how many findings matched no node.”
• “Cross-reference the CodeQL findings with blast radius data for the payments module.”

Requirements

• Trailmark, installed with uv
• SARIF results or weAudit annotation files to import

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

1. 1Finding file path is normalized relative to the graph's root_path
2. 2Nodes whose location.file_path matches AND whose line range overlaps are
3. 3The tightest match (smallest span) is preferred
4. 4If a finding's location doesn't overlap any node, it counts as unmatched

What it can do on your machine

Read from SKILL.md and the folder at commit 82fe822. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • uv
  • semgrep

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Audit Findings Graph Overlay loads about 2.3k tokens when it runs, and up to ~3.2k if it reads all its reference files. Until then it costs about 163 tokens; SKILL.md has 784 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~163

When it runs · the whole SKILL.md, loaded when a task matches

~2.3k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~3.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from trailofbits/skills at commit 82fe822, republished under its CC-BY-SA-4.0 licence (© trailofbits). 784 words, ~2,333 tokens.

name

audit-augmentation

description

Augments Trailmark code graphs with external audit findings from SARIF static analysis results, weAudit annotation files, and version-gated Trailmark 0.4.x binary-analysis graph exports. 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, etc.). Use when projecting SARIF results onto a code graph, overlaying weAudit annotations, importing binary graph findings, cross-referencing Semgrep, CodeQL, or binary-analysis findings with call graph data, or visualizing audit findings in the context of code structure.

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

if not hasattr(engine, "augment_binary"):
    raise RuntimeError("Binary augmentation requires Trailmark >= 0.4.0")

# Augment with SARIF
uv run trailmark augment {targetDir} --sarif results.sarif

# Augment with weAudit
uv run trailmark augment {targetDir} --weaudit .vscode/alice.weaudit

# Both at once, output JSON
uv run trailmark augment {targetDir} \
    --sarif results.sarif \
    --weaudit .vscode/alice.weaudit \
    --json

from trailmark.query.api import QueryEngine

engine = QueryEngine.from_directory("{targetDir}", language="auto")

# Run pre-analysis first for cross-referencing
engine.preanalysis()

# Augment with SARIF
result = engine.augment_sarif("results.sarif")
# result: {matched_findings: 12, unmatched_findings: 3, subgraphs_created: [...]}

# Augment with weAudit
result = engine.augment_weaudit(".vscode/alice.weaudit")

# Augment with an external binary graph export (v0.4+)
if hasattr(engine, "augment_binary"):
    result = engine.augment_binary("binary_graph.json")

# Query findings
engine.findings()                                       # All findings
engine.subgraph("sarif:error")                          # High-severity SARIF
engine.subgraph("weaudit:high")                         # High-severity weAudit
engine.subgraph("sarif:semgrep")                        # By tool name
engine.annotations_of("function_name")                  # Per-node lookup

Augmentation Progress:
- [ ] Step 1: Build graph and run pre-analysis
- [ ] Step 2: Locate SARIF/weAudit/binary graph files
- [ ] Step 3: Run augmentation
- [ ] Step 4: Inspect results and subgraphs
- [ ] Step 5: Cross-reference with pre-analysis

engine = QueryEngine.from_directory("{targetDir}", language="auto")
engine.preanalysis()

{
  "artifact": {"name": "libexample", "architecture": "x86_64", "sha256": "..."},
  "functions": [
    {"symbol": "parse_packet", "address": "0x401000",
     "source": {"file": "src/parser.c", "line": 42}}
  ],
  "calls": [
    {"source": "parse_packet", "target": "malloc", "confidence": "inferred"}
  ]
}

© trailofbits, CC-BY-SA-4.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references, assets) in plugins/trailmark/skills/audit-augmentation of trailofbits/skills.

• SKILL.md
• agents/openai.yaml
• assets/trail-of-bits-mark.svg
• references/formats.md

Open the folder on GitHubat commit 82fe822