@trailofbits
Organization
More code: binary lifters @lifting-bits, blockchain @crytic, forks @trail-of-forks
95 skills1 repository 7.7K
Prepare a regression investigation by fixing the exact before and after source versions, preserving PR or commit context, and producing a sealed preparation record that explains change boundaries and evidence collection limits.
Handle one known local bug or testable bug hypothesis through reproduction, independent validation, repair, and regression checks. Produce a local patch commit and evidence reports that help reviewers judge whether the fix is ready.
Repair one independently confirmed local bug by addressing the rule the code violates and checking related variants within scope. Deliver regression tests, before and after test results, separate patch files, and one local commit.
Independently rerun an unchanged bug reproduction package before repair. Check whether compiler diagnostics or runtime assertions support the exact reported claim, then preserve execution evidence and record a confirmed, unconfirmed, or inconclusive judgment.
Build and run systems before and after a change, then execute the same reproduction procedure against both. Save environment details, inputs, commands, and separate logs to document observed behavior and any setup blockers.
Independently verifies a committed security patch by testing the original, patched, and fully reverted code. It preserves test evidence, checks the declared repair scope, and reports confirmed failures, missing evidence, and limits of what was proven.
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.
Independently rerun supplied proof-of-concept code against freshly built versions from before and after a change. Compare observed behavior, verify reachability through real interfaces, and preserve separate logs showing agreement, divergence, or blockers.
Coordinate investigations into regressions introduced by PRs or commits. Assign preparation, discovery, reproduction, independent verification, decisions, and reporting to separate stages, while preserving evidence and progress records for later resumption.
Turn saved regression decisions into evidence-linked HTML, Markdown, and JSON reports. Validate records and coverage, preserve assigned ratings, and distinguish confirmed defects from existing bugs, rejected claims, and unresolved work.
Independently reproduce a reported runtime or compiler bug in a local repository. Build the baseline, exercise the actual artifact or compiler, and save logs and structured records distinguishing reproduction, absence of the behavior, and setup blockers.
Review a specific code change and trace its callers to identify behavior that may have broken. Record suspected regressions, reachable triggers, evidence needs, and coverage gaps so a separate reproduction step can investigate them.
Diagnose Claude in Chrome connection failures on macOS by checking native messaging hosts, the processes linking Chrome to Claude, and their settings. It guides fixes for competing configurations, stale wrappers, and session conflicts, including restart steps.
Connect static analysis results and human audit notes to a Trailmark code graph. Group findings by severity and compare them with input flow, impact, and privilege boundaries to prioritize investigation and understand findings in their code context.
Create dictionaries of keywords and identifying byte sequences for fuzzing, or testing with generated inputs. Extract useful entries from code, binaries, or specifications, then configure fuzzers to explore parsing paths beyond initial input validation.
Get a quick structural overview of a codebase with Trailmark. The skill identifies programming languages, counts entry points where execution begins, and returns dependency information to support orientation before deeper analysis.
Select relevant code using Trailmark's map of function relationships, then delegate explanation, review, or edit proposals to a smaller model. Limit the supplied source, check cited evidence, and verify proposed changes before applying them.
Create Mermaid diagrams from code relationships parsed by Trailmark. Visualize function calls, class inheritance, module dependencies, class members, complexity hotspots, and paths from inputs to sensitive functions, with adjustable focus, depth, and layout.
Set up libFuzzer to test C/C++ code with varied inputs guided by which code paths run. Build test harnesses, manage sample inputs and dictionaries, enable error detectors, and reproduce crashes or investigate stalled coverage.
Analyze code structure with Trailmark to identify complex functions, trace input flow, assess impact across connected code, and locate privilege boundaries. The resulting JSON provides detailed evidence for deciding where to focus a code audit.
Test cryptographic code for timing side channels, where execution time can reveal secrets. Use dudect to detect statistical differences and Timecop with Valgrind to trace secret-dependent operations, then interpret results and retest changes.
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.
Identify checks and changing global state that block fuzzing, then adjust them in fuzzing builds. The skill covers targeted validation bypasses, repeatable behavior, coverage comparisons, and checks for false crash reports introduced by patches.
Audit C/C++ and Rust code for secrets left in memory. It checks missing or incomplete wipes, examines compiler output for removed cleanup operations, and produces reports with evidence and suggested fixes.
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