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Searches and explores Burp Suite project files (.burp) from the command line. Use when searching response headers or bodies with regex patterns, extracting security audit findings, dumping proxy history or site...
Techniques for writing effective fuzzing harnesses across languages. Use when creating new fuzz targets or improving existing harness code.
Clarify requirements before implementing. Use when serious doubts araise.
Atheris is a coverage-guided Python fuzzer based on libFuzzer. Use for fuzzing pure Python code and Python C extensions.
Comprehensive smart contract development advisor based on Trail of Bits' best practices. Analyzes codebase to generate documentation/specifications, review architecture, check upgradeability patterns, assess im...
Techniques for patching code to overcome fuzzing obstacles. Use when checksums, global state, or other barriers block fuzzer progress.
CodeQL is a static analysis framework that queries code as a database. Use when you need interprocedural analysis or complex data flow tracking.
Systematic code maturity assessment using Trail of Bits' 9-category framework. Analyzes codebase for arithmetic safety, auditing practices, access controls, complexity, decentralization, documentation, MEV risk...
AFL++ is a fork of AFL with better fuzzing performance and advanced features. Use for multi-core fuzzing of C/C++ projects.
Run Semgrep static analysis for fast security scanning and pattern matching. Use when asked to scan code with Semgrep, write custom YAML rules, find vulnerabilities quickly, use taint mode, or set up Semgrep in...
Verifies code implements exactly what documentation specifies for blockchain audits. Use when comparing code against whitepapers, finding gaps between specs and implementation, or performing compliance checks f...
Performs security-focused differential review of code changes (PRs, commits, diffs). Adapts analysis depth to codebase size, uses git history for context, calculates blast radius, checks test coverage, and gene...
Enables ultra-granular, line-by-line code analysis to build deep architectural context before vulnerability or bug finding.
Detects timing side-channel vulnerabilities in cryptographic code. Use when implementing or reviewing crypto code, encountering division on secrets, secret-dependent branches, or constant-time programming quest...
Coverage analysis measures code exercised during fuzzing. Use when assessing harness effectiveness or identifying fuzzing blockers.
Verifies that git commits address security audit findings without introducing bugs. This skill should be used when the user asks to "verify these commits fix the audit findings", "check if TOB-XXX was addressed...
Run CodeQL static analysis for security vulnerability detection, taint tracking, and data flow analysis. Use when asked to analyze code with CodeQL, create CodeQL databases, write custom QL queries, perform sec...
Guide you through Trail of Bits' 5-step secure development workflow. Runs Slither scans, checks special features (upgradeability/ERC conformance/token integration), generates visual security diagrams, helps doc...
Use when interpreting Culture Index surveys, CI profiles, behavioral assessments, or personality data. Supports individual interpretation, team composition (gas/brake/glue), burnout detection, profile compariso...
Prepare your codebase 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 com...
Constant-time testing detects timing side channels in cryptographic code. Use when auditing crypto implementations for timing vulnerabilities.
LibAFL is a modular fuzzing library for building custom fuzzers. Use for advanced fuzzing needs, custom mutators, or non-standard fuzzing targets.
Parse, analyze, and process SARIF (Static Analysis Results Interchange Format) files. Use when reading security scan results, aggregating findings from multiple tools, deduplicating alerts, extracting specific...
Identifies error-prone APIs, dangerous configurations, and footgun designs that enable security mistakes. Use when reviewing API designs, configuration schemas, cryptographic library ergonomics, or evaluating w...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.