trailmark-finding-triage
Performs graph-assisted triage of a single security finding, SARIF result, weAudit annotation, suspicious function, or report excerpt using Trailmark reachability, entrypoint paths, taint, privilege-boundary, blast-radius, caller/callee, and neighborhood evidence. Use when deciding whether one candidate issue is reachable, prioritizing a finding before PoC work, preparing evidence for exploit validation, or checking whether a static-analysis result is actionable.
git clone --depth 1 https://github.com/trailofbits/skills /tmp/trailmark-finding-triage && cp -r /tmp/trailmark-finding-triage/plugins/trailmark/skills/trailmark-finding-triage ~/.claude/skills/trailmark-finding-triageSKILL.md
# Trailmark Finding Triage Build a concise graph evidence packet for one candidate finding. This skill answers whether the affected code is reachable, what graph evidence supports or weakens the claim, and what manual review is still required before calling the issue exploitable. ## When to Use - Triage one static-analysis result before spending PoC time - Check whether a manual finding is entrypoint-reachable - Build an evidence packet for PoC work - Review a single suspicious function discovered during manual audit - Decide whether one issue should be promoted, deprioritized, or treated as part of a broader chain analysis ## When NOT to Use - Multiple weak findings might compose into a stronger chain. Use a chain or composition workflow instead. - The user wants a full audit. Use an audit or design-review workflow instead. - The user wants remediation verification for a known finding. Use a remediation-review workflow instead. - The target is a PR or branch diff. Use `graph-evolution` plus a differential review workflow. - No concrete finding, function, file/line, or suspicious sink exists yet. Use discovery skills first. ## Rationalizations to Reject | Rationalization | Why It Is Wrong | Required Action | |---|---|---| | "The scanner says high severity, so reachability is obvious" | Static findings need graph and code context before promotion | Bind the finding to a graph node and check entrypoint paths | | "No entrypoint path means impossible" | It may mean parser, proxy, or dynamic dispatch limitations | Report the limitation separately from reachability | | "An auth check appears on the path, so the issue is safe" | The check may enforce the wrong predicate or be bypassed by another path | Treat validation/auth as review targets, not proof | | "One reachable path is enough for a PoC claim" | The path still needs attacker-controlled inputs and compatible preconditions | Separate graph reachability from exploitability | | "This is probably a chain" | Single-finding triage stops at one candidate | Hand off related findings to a composition workflow | ## Workflow ``` Finding Triage Progress: - [ ] Step 1: Normalize the candidate - [ ] Step 2: Build or reuse the Trailmark graph - [ ] Step 3: Bind the candidate to graph node(s) - [ ] Step 4: Analyze reachability, taint, boundaries, and blast radius - [ ] Step 5: Decide and emit the evidence packet ``` ### Step 1: Normalize the Candidate Accept file/line, function name, SARIF result, weAudit annotation, Markdown finding excerpt, or a manual claim. Normalize it to: - title - source type - file path and line range if present - function or node hint - suspected source, sink, or asset - claimed impact If there is no concrete code anchor, stop and ask for one. For input handling details, see [references/input-normalization.md](references/input-normalization.md). ### Step 2: Build Or Reuse The Graph Use the public `trailmark` skill workflow. Prefer an existing fresh exported graph or `.trailmark/` artifact when present. Otherwise build a graph with `language="auto"` or the target's explicit language list, then run `engine.preanalysis()`. Record the Trailmark version or feature probes used. Feature-gate Trailmark 0.4-only APIs with `hasattr()` or CLI help checks. ### Step 3: Bind The Candidate Bind by file and line overlap first, then function name plus file. If several nodes match, list every candidate and select the narrowest enclosing node as primary. If no node matches, report a binding limitation instead of guessing. SARIF and weAudit users should reuse the `audit-augmentation` workflow for matching and then inspect the annotated node. ### Step 4: Analyze Graph Evidence Run the query recipe in [references/query-recipes.md](references/query-recipes.md): - entrypoint paths to the bound node - trust level of each path when available - membership in `tainted`, `privilege_boundary`, and `high_blast_radius` subgraphs - direct callers and callees - high-impact downstream sinks - sibling or nearby nodes worth manual review Do not treat graph reachability as proof of exploitability. ### Step 5: Decide And Handoff Produce one verdict: | Verdict | Meaning | |---|---| | `Promote` | Graph evidence supports reachability and plausible impact | | `Needs manual review` | Evidence is suggestive but not decisive | | `Deprioritize` | No reachable path or only trusted/internal paths found | | `Blocked` | Binding or Trailmark analysis failed | Write the evidence packet using [references/output-format.md](references/output-format.md). Hand off promoted PoC-worthy issues to the user's PoC workflow. Hand off related findings to a composition workflow. Hand off repeatable root causes to `trailmark-variant-neighborhood`, `variant-analysis`, or a custom Semgrep/CodeQL rule workflow. ## Example Prompts - "Use Trailmark finding triage on `src/Vault.sol:148`; I think withdraw can bypass the balance update." - "Triage this SARIF result before I spend PoC time: `semgrep:error unchecked-transfer` in `contracts/Bridge.sol` line 91." - "This report excerpt claims `parse_packet` is attacker reachable. Build the Trailmark evidence packet and tell me what is still missing."
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches AI agents running in CI/CD pipelines, including env var intermediary patterns, direct expression injection, dangerous sandbox configurations, and wildcard user allowlists. Use when reviewing workflow files that invoke AI coding agents, auditing CI/CD pipeline security for prompt injection risks, or evaluating agentic action configurations.
Clarify requirements before implementing. Use when serious doubts arise.
Understand a codebase before looking for bugs in it - what each function assumes, what it guarantees, and what it depends on elsewhere. Use when starting an audit, threat model, or architecture review on unfamiliar code, and before any vulnerability-hunting pass.
Scans Algorand smart contracts for 11 common vulnerabilities including rekeying attacks, unchecked transaction fees, missing field validations, and access control issues. Use when auditing Algorand projects (TEAL/PyTeal).
Prepares codebases for security review using Trail of Bits' checklist. Helps set review goals, runs static analysis tools, increases test coverage, removes dead code, ensures accessibility, and generates documentation (flowcharts, user stories, inline comments). Use when preparing your own codebase to be audited by someone else, getting a repository review-ready before an external security review, deciding what to fix before auditors start, or asking what assessors need from a project. For understanding unfamiliar code you are about to audit, use audit-context-building instead.
Scans Cairo/StarkNet smart contracts for 6 critical vulnerabilities including felt252 arithmetic overflow, L1-L2 messaging issues, address conversion problems, and signature replay. Use when auditing StarkNet projects.
Systematic code maturity assessment using Trail of Bits' 9-category framework. Analyzes codebase for arithmetic safety, auditing practices, access controls, complexity, decentralization, documentation, MEV risks, low-level code, and testing, then produces a scorecard with evidence-based ratings and a priority-ordered roadmap. Use when assessing or scoring the maturity of a smart contract or blockchain codebase, producing a maturity scorecard or evaluation, or judging how mature, well-tested, or well-documented such a project is against a rubric.
Scans Cosmos SDK blockchain modules and CosmWasm contracts for consensus-critical vulnerabilities — chain halts, fund loss, state divergence. 25 core + 16 IBC + 10 EVM + 3 CosmWasm patterns. Use when auditing custom x/ modules, reviewing IBC integrations, or assessing pre-launch chain security. Updated for SDK v0.53.x.