Skip to content
cccskills
FreePublished on GitHub

trailmark-variant-neighborhood

Uses a known or suspected vulnerability to find related code through Trailmark's graph of calls, types, and implementations. Produces ranked review targets with reasons and limitations for follow-up security analysis.

OriginalShow the original description

Expands one confirmed or suspected vulnerability into a Trailmark graph neighborhood of variant candidates by finding sibling functions, shared callers and callees, common sensitive sinks, common entrypoint paths, interface implementations, override relationships, type/reference neighbors, and structurally similar nodes. Use after one issue is found to seed variant-analysis, semgrep-rule-creator, static-analysis, or manual review with graph-derived candidate locations.

See how to install

Good for

  • Finding variants of a known vulnerability
  • Prioritizing code that shares sensitive operations
  • Preparing candidates for Semgrep or CodeQL review
  • Planning manual review of related implementations

Files included (6)

  • SKILL.md4.2 KB
  • agents/openai.yaml252 B
  • assets/trail-of-bits-mark.svg3.0 KB
  • references/neighborhood-patterns.md2.2 KB
  • references/output-format.md1.4 KB
  • references/ranking.md1.6 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Trailmark Variant Neighborhood

Expand one seed issue into graph-derived variant candidates. This skill generates review targets, not confirmed findings.

When to Use

  • A finding is confirmed or plausible and variants may exist
  • The vulnerable pattern depends on call context
  • The issue involves a shared sink, source, validator, interface, override, trait, hook, handler, adapter, or critical type
  • The next step is to seed variant-analysis, semgrep-rule-creator, static-analysis, or manual review

When NOT to Use

  • No seed issue exists. Use discovery or triage first.
  • The pattern is purely syntactic and already obvious. Use semgrep-rule-creator directly.
  • The question is exploit-chain composition across multiple findings. Use a composition workflow.
  • The goal is remediation verification. Use a remediation-review workflow.
  • The seed cannot be bound to a graph node.

Rationalizations to Reject

RationalizationWhy It Is WrongRequired Action
"Nearby code means variant"Proximity is only a candidate reasonRank it as a review target
"Only exact same names matter"Variants often share sinks or preconditions, not namesExpand across callers, callees, interfaces, and types
"Every candidate is a finding"This skill outputs candidates for reviewAvoid vulnerability claims
"Unreachable candidates can be ignored completely"They may become reachable after refactorsRank lower or list as deferred
"Graph candidates replace semantic pattern work"Graph structure finds locations, not root-cause semanticsHand off to variant-analysis, Semgrep, CodeQL, or manual review

Workflow

Variant Neighborhood Progress:
- [ ] Step 1: Normalize and bind the seed
- [ ] Step 2: Expand graph neighborhoods
- [ ] Step 3: Rank candidates
- [ ] Step 4: Extract variant pattern guidance
- [ ] Step 5: Emit handoff packet

Step 1: Normalize And Bind The Seed

Accept finding text, file/line, function name, or output from trailmark-finding-triage. Bind the seed to a Trailmark node and record the root cause in plain language.

If the seed has no concrete graph binding, stop before inventing variants.

Step 2: Expand Neighborhoods

Use the dimensions in references/neighborhood-patterns.md:

  • shared callers
  • shared callees and sinks
  • entrypoint path neighbors
  • interface, override, trait, and implementation siblings
  • file or module cluster neighbors
  • taint or privilege-boundary peers
  • type and state-reference neighbors

Bound expansion to avoid candidate floods.

Step 3: Rank Candidates

Rank with references/ranking.md. Prioritize entrypoint-reachable, tainted, boundary-adjacent, high-blast-radius, shared sink, same-interface, and close-distance candidates. Penalize test, mock, generated, vendor, unreachable, and trusted-internal-only candidates.

Step 4: Extract Pattern Guidance

Summarize what should be searched for syntactically and what requires semantic review. Identify whether follow-up belongs in:

  • variant-analysis
  • semgrep-rule-creator
  • static-analysis with CodeQL or SARIF-producing tools
  • manual review

Step 5: Emit Handoff Packet

Use references/output-format.md. Include ranked candidates, inclusion reasons, exclusions, limitations, and the variant-analysis handoff.

Stop Conditions

  • No graph binding exists
  • Candidate count is too high and the root cause is underspecified
  • Trailmark cannot analyze the target language
  • The seed is only in test, generated, or vendor code and the user did not say that code is in scope

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Build and test code with AddressSanitizer, a tool that detects invalid memory access during execution. Configure checks for C/C++ and unsafe Rust, investigate crash reports, and adjust settings for fuzzing, or testing with generated inputs.

  • Detect memory errors while fuzzing C/C++
  • Test unsafe Rust and calls to external libraries
  • Interpret an ASan crash report
trailofbits/skills7.7KUpdated Oct 22, 2026

Assess source code and live reproduction evidence to decide whether a change introduced a regression, a newly caused defect. Record supported conclusions, exclusions, severity, and unresolved gaps in an evidence-linked decision file.

  • Decide whether a change introduced a new defect
  • Separate existing bugs from newly introduced defects
  • Record missing evidence and unresolved questions
trailofbits/skills7.7KUpdated Oct 22, 2026

aflpp

FreeSummary

Sets up AFL++ to test C/C++ programs with varied generated inputs, a technique called fuzzing. Covers running tests across CPU cores, monitoring progress, reducing input collections, and reproducing crashes for investigation.

  • Running C/C++ fuzzing across multiple CPU cores
  • Exploring further after libFuzzer progress stalls
  • Monitoring fuzzing progress and stability
trailofbits/skills7.7KUpdated Oct 22, 2026

Audits GitHub Actions workflows that run AI coding agents. Traces how attacker-controlled content reaches prompts, checks permissions and sandbox settings, and reports evidence, severity, and fixes for prompt injection and related configuration risks.

  • Reviewing workflows that run AI coding agents
  • Tracing issue and PR content into agent prompts
  • Checking sandbox settings and user allowlists
trailofbits/skills7.7KUpdated Oct 22, 2026

Reviews Algorand smart contracts written in TEAL or PyTeal for 11 vulnerability patterns. Produces a complete coverage table and findings with code references, severity ratings, and suggested fixes, with optional automated checks using Tealer.

  • Security checks before an Algorand contract audit
  • Reviewing TEAL or PyTeal transaction validation
  • Verifying fixes for reported vulnerabilities
trailofbits/skills7.7KUpdated Oct 22, 2026

atheris

FreeSummary

Set up Atheris to test Python code and C extensions with automatically varied inputs. It guides test harness creation, coverage tracking to explore more code, and AddressSanitizer setup for finding memory errors.

  • Fuzzing a Python package or parser
  • Investigating memory corruption in Python C extensions
  • Turning raw bytes into typed test arguments
trailofbits/skills7.7KUpdated Oct 22, 2026

See all skills by trailofbits

Report a problem with this skill