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Libafl

Listed
trailofbits·vlatest·testing·CC-BY-SA-4.0

Libafl efficiently converts arbitrary binary data into a compact, executable format for fast analysis and debugging.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add trailofbits/skills --skill libafl -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

trailofbits

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 2 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 3 hosts that are neither well-known infrastructure nor declared in the skill's frontmatter: apt.llvm.org, downloads.sourceforge.net, sh.rustup.rs.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    apt.llvm.orgundeclaredsh.rustup.rsundeclareddownloads.sourceforge.netundeclaredraw.githubusercontent.comsource host

    What it found

    • plugins/testing-handbook-skills/skills/libafl/SKILL.md:68contacts apt.llvm.org
      wget https://apt.llvm.org/llvm.sh
    • plugins/testing-handbook-skills/skills/libafl/SKILL.md:82contacts sh.rustup.rs
      curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
    • plugins/testing-handbook-skills/skills/libafl/SKILL.md:497contacts downloads.sourceforge.net
      curl -L -O https://downloads.sourceforge.net/project/libpng/libpng16/1.6.37/libpng-1.6.37.tar.xz

  • No pipe-to-shell installers: failed

    Runs code fetched at install time in 1 place.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

    What it found

    • plugins/testing-handbook-skills/skills/libafl/SKILL.md:82remote script piped into a shell
      curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • Pinned to a commit: passed

    Scanned trailofbits/skills at 82fe822625.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
82fe822625
Manifest
plugins/testing-handbook-skills/skills/libafl/SKILL.md
Scanned
2 files, 537 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

libafl is an instrumentation-based, feedback-driven fuzzing engine. It allows you to automatically discover new test cases for software by mutating existing inputs and monitoring program behavior. This helps identify vulnerabilities and improve the robustness of applications through targeted testing.

When to use it

  • Security Auditing: To find security flaws in closed-source or complex systems where manual testing is insufficient.
  • Regression Testing: To ensure that code changes haven't introduced new bugs or broken existing functionality.
  • Performance Optimization: Identify performance bottlenecks by observing how the software responds to various inputs.
  • Driver Development: Test and improve the reliability of device drivers in a systematic way.

Key capabilities

  • Instrumentation-based fuzzing
  • Feedback-driven test case generation
  • Automated vulnerability discovery
  • Regression testing support

Example prompts

  • "Fuzz the my_program binary using libafl, focusing on input parsing."
  • "Run libafl to find crashes in the image processing library."
  • "Can you use libafl to test this network protocol implementation?"

Tips & gotchas

libafl requires a degree of familiarity with fuzzing concepts and potentially some code modification for instrumentation. The effectiveness depends heavily on proper setup and understanding of the target program's behavior.