kernel-exploitation

kernel-exploitation is a skill for Claude Code, Codex from yaklang/hack-skills. It costs 54 tokens per session (2,952 once invoked), scanned B, original, MIT.

A guide to finding and exploiting flaws in the Linux kernel, the core software that controls a computer’s hardware and permissions. It covers bugs such as use-after-free, out-of-bounds access, race conditions, and type confusion.

In plain words
What is it for?
It helps analyze kernel vulnerabilities, set up test environments with QEMU, bypass protections, and build privilege-escalation exploits using techniques such as kernel ROP and heap manipulation.
Why use it?
Kernel bugs can let a normal user gain administrator-level control, but kernel memory protections and rules differ from ordinary application attacks. The guide helps apply the right methods in security challenges and real vulnerability research.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is cpio -idmv < ../rootfs.cpio.gz.

Good fit It helps analyze kernel vulnerabilities, set up test environments with QEMU, bypass protections, and build privilege-escalation exploits using techniques such as kernel ROP and heap manipulation.

Compare 6 skills from other repositories ↓
About the project

HackSkills is an organized knowledge base of installable skills that gives AI agents practical security knowledge across areas such as web security, privilege escalation, reverse engineering, and digital forensics. It is intended for bug bounty work, penetration testing, CTF competitions, and authorized security research. The catalogue entries are the project's own master, category, and topic skills.

yaklang/hack-skills · 2,521 stars · on GitHub

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/yaklang/hack-skills
agentmods
npx agentmods add skills/yaklang/hack-skills/kernel-exploitation

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for kernel-exploitation

README.md
[![agentmods](https://agentmods.dev/badge/skills/yaklang/hack-skills/kernel-exploitation/github.svg)](https://agentmods.dev/skills/yaklang/hack-skills/kernel-exploitation)
Your own site
<a href="https://agentmods.dev/skills/yaklang/hack-skills/kernel-exploitation"><img src="https://agentmods.dev/badge/skills/yaklang/hack-skills/kernel-exploitation/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for kernel-exploitation

Your own site · 80×15
<a href="https://agentmods.dev/skills/yaklang/hack-skills/kernel-exploitation"><img src="https://agentmods.dev/badge/skills/yaklang/hack-skills/kernel-exploitation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,952 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket warn 15 Sept 2026
  • Snyk pass 15 Sept 2026
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 5 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high YARA Match · line 105
    YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).
    Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
  • high Tool Misuse · line 146
    Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).
    Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
  • high Tool Misuse · line 146
    Tool calls are chained to bypass individual safety checks or escalate capabilities beyond what any single tool call would allow.
    Fix: Limit tool chaining depth and validate the output of each tool before passing it to the next. Require explicit user approval for multi-step chains.
  • medium Privilege Escalation · line 146
    Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.
    Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
  • low Privilege Escalation · line 38
    Skill requests more permissions than appear necessary for its stated functionality. Review if elevated access is justified.
    Fix: Request only the minimum permissions required. Document why each permission is needed. Remove broad permissions like '*' or 'all'.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00054 $0.02952
Opus 5.5 $0.00022 $0.01181
Sonnet 5.5 $0.00011 $0.00590
Haiku 4.5 $0.00005 $0.00295

Measured 1mo ago against content hash 9f5deef00930, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade B, and why

kernel-exploitation scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

echo 'cp /flag /tmp/flag && chmod 777 /tmp/flag' >> /tmp/x

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

wget https://cdn.kernel.org/pub/linux/kernel/v6.x/linux-6.1.tar.xz
Origin

Copies of this mod

6 near-identical copies found in the catalogue:

skills/kernel-exploitation/SKILL.md · 308 lines

How it starts

The opening of the file, as written. The whole thing — 308 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SKILL: Linux Kernel Exploitation — Expert Attack Playbook

AI LOAD INSTRUCTION: Expert kernel exploitation techniques. Covers environment setup (QEMU), vulnerability classes, privilege escalation targets, kernel ROP, ret2usr, stack pivoting, and cross-cache attacks. Distilled from ctf-wiki kernel-mode sections and real-world kernel CVEs. Base models often confuse user-mode and kernel-mode exploitation constraints, especially regarding SMEP/SMAP/KPTI.

Advanced References


1. EXPLOITATION MODEL

┌─────────────────────────────────────────────────────┐
│  1. Find Vulnerability                              │
│     (UAF, OOB, race, integer overflow, type confusion)│
├─────────────────────────────────────────────────────┤
│  2. Build Primitive                                 │
│     (arbitrary read, arbitrary write, controlled RIP)│
├─────────────────────────────────────────────────────┤
│  3. Bypass Mitigations                              │
│     (KASLR, SMEP, SMAP, KPTI)                     │
├─────────────────────────────────────────────────────┤
│  4. Escalate Privileges                             │
│     (commit_creds, modprobe_path, namespace escape)  │
├─────────────────────────────────────────────────────┤
│  5. Return to Userspace Cleanly                     │
│     (KPTI trampoline, iretq/sysretq, swapgs)       │
└─────────────────────────────────────────────────────┘

Read the full file on GitHub · 308 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 308 lines · 54 tokens per session scan B 9f5deef00930

Subscribe to this mod's changes

kernel-exploitation is a skill published in the GitHub repository yaklang/hack-skills (2,521 stars, last pushed 1mo ago), licensed MIT. It adds 54 tokens to every session and 2,952 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it B with 2 findings (asks for root, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens