테스트·보안 스킬

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Prepare source versions for a regression investigation
• Preserve PR discussions and review comments
• Document change boundaries and collection limits

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Compare behavior before and after a change
• Create a portable procedure to reproduce a suspected defect
• Record environments, commands, and execution logs

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Independently verify a security patch
• Compare original, patched, and reverted behavior
• Check valid inputs for regressions

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate and repair one reported local bug
• Have separate agents verify reproduction and the fix
• Prepare evidence reports for patch review

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Independently verify a bug reproduction before repair
• Recheck compiler errors or runtime assertions
• Document uncertain or unreliable reproduction evidence

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reproduce a reported runtime bug locally
• Verify a compiler failure using its diagnostic
• Preserve logs and records for a reproduction handoff

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Compile saved decisions into a regression report
• Refresh reports after evidence or decisions change
• Review coverage gaps and unresolved findings

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate regressions across PRs or commits
• Coordinate staged work across multiple agents
• Resume an investigation from saved progress

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Independently check a supplied reproduction result
• Compare behavior before and after a change
• Verify reachability with the claimed access level

Build a graph of functions and calls across multiple programming languages to investigate entry points, paths to sensitive operations, and potential impact. Use the results to prioritize security reviews and connect external findings with source code.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Tracing call paths from entry points to sensitive functions
• Prioritizing code for a security audit
• Connecting calls across language and RPC boundaries

Evaluate vulnerability reports using seven practical criteria, including attacker capabilities, real usage, documented behavior, and remediation costs. Produce a reasoned decision to accept, dismiss, or request more evidence before committing to deeper investigation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Screening AI-generated security findings before human review
• Assessing whether a reported CVE warrants investigation
• Reviewing bug bounty submissions

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Connecting Semgrep or CodeQL results to code structure
• Combining human audit notes with automated findings
• Prioritizing findings using input flow and impact

Measure which code fuzzing reaches as it tries many generated inputs. Use coverage reports to find unreachable areas, compare progress, and guide improvements to test harnesses, starting inputs, or dictionaries of useful input values.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Establish initial coverage for a fuzzing run
• Investigate why fuzzing stops reaching new code
• Compare coverage before and after harness changes

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking cryptographic functions for secret-dependent timing
• Measuring timing differences in compiled binaries
• Tracing the cause of a suspected timing leak

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Running C/C++ fuzzing across multiple CPU cores
• Exploring further after libFuzzer progress stalls
• Monitoring fuzzing progress and stability

Assess a single suspected security issue using Trailmark's graph of code relationships. Gather evidence about reachable paths, input flow, and potential impact, then receive a priority verdict and a list of remaining manual checks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Prioritizing a static analysis finding before proof-of-concept work
• Checking whether entry points can reach a suspicious function
• Preparing code evidence for exploit validation

Turn a Mermaid sequence diagram of a cryptographic protocol into a ProVerif model, a file for formal security checks. It includes queries for secrecy, authentication, replay resistance, and forward secrecy where applicable.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Converting a cryptographic protocol diagram into a .pv file
• Preparing session key secrecy checks
• Modeling authentication and replay resistance

Builds and improves C/C++ and Rust fuzzing harnesses, the entry points that feed generated test data into code. Helps structure inputs, reach more code paths, and address crashes caused by inconsistent test behavior.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Writing a first fuzzing harness
• Building structured inputs for an API
• Investigating crashes that cannot be reproduced

Build a custom fuzzer, a tool that tests code with many generated inputs, using LibAFL in Rust. Combine input mutation, execution feedback, scheduling, and target execution components when standard fuzzers offer insufficient control.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a fuzzer for a nonstandard target or architecture
• Implement custom input mutation and feedback strategies
• Prototype a new fuzzing research technique

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a dictionary for JSON or XML parser fuzzing
• Add protocol keywords to generated test inputs
• Test image parsers with file signatures and chunk names

Compare code structure across two commits, tags, or directories to identify security-relevant changes. Produces a report on new attack paths, privilege boundaries, complexity, and how widely a change could affect other functions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Compare code structure before a release
• Investigate new attack paths after code changes
• Track untrusted data flows across a refactor

Find other occurrences of a known bug across a codebase by tracing its root cause. Gradually broaden search patterns, assess matching candidates, assign severity, and document findings with rules to help prevent recurrence.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding similar issues after discovering a vulnerability
• Building CodeQL or Semgrep queries from a known bug
• Checking whether similar code shares the same root cause

Guides fuzz testing for Ruby libraries and gems with Ruzzy, using varied inputs to find failures. Covers pure Ruby and C extensions, including test harnesses, memory error detection, environment setup, and crash reproduction.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding fuzz tests to a Ruby library
• Testing memory safety in a gem's C extension
• Preparing tracer and harness scripts for pure Ruby