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Exploit Development

Community
hypnguyen1209
exploit-development

Use when turning a memory-corruption bug into a working PoC — stack/ROP, glibc heap & FSOP, format strings, browser/JIT type confusion & UAF, Linux/Windows kernel LPE against ASLR/DEP/CFG/CET/V8-Sandbox

Overview

Publisherhypnguyen1209
Repositoryoffensive-claude
Skill nameexploit-development
Stars
396
Forks
71
Bundled files
15
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 15 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by hypnguyen1209 on GitHub. Read the source before you install it.

Installation

Install the Exploit Development AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/hypnguyen1209/offensive-claude/tree/main/skills/exploit-development
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/hypnguyen1209/offensive-claude.git /tmp/offensive-claude
mkdir -p .claude/skills
cp -r /tmp/offensive-claude/skills/exploit-development .claude/skills/exploit-development
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Exploit Development in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Exploit Development on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Exploit Development is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Exploit Development

End-to-end weaponization: turn a confirmed bug class into a reliable, version-pinned PoC, then a primitive chain (leak -> R/W -> control flow), against current mitigations. Every cluster pairs the offensive path with detection telemetry and OPSEC.

When to Activate

  • A confirmed vulnerability needs a working, reliable PoC (>=90% success target).
  • Userland binary exploitation: stack overflow, heap (UAF/overflow/double-free), format string.
  • Defeating modern mitigations: ASLR/PIE, NX/DEP, stack canaries, Full RELRO, CFG, Intel CET shadow stack, V8 Sandbox/pointer compression.
  • Browser/JIT engine exploitation (V8 type confusion, addrof/fakeobj, WASM jump-table pivot).
  • Local privilege escalation via Linux/Windows kernel memory corruption.
  • Converting a crash into a stable read/write/execute primitive chain.

Technique Map

TechniqueATT&CKCWEReferenceScript
Stack overflow -> ret2libc/ROPT1203CWE-121references/stack-rop-mitigations.mdscripts/offset_finder.py
ret2csu / SROP / stack pivotT1203CWE-121references/stack-rop-mitigations.mdscripts/rop_autochain.py
ret2dlresolve (leakless)T1203CWE-121references/stack-rop-mitigations.mdscripts/rop_autochain.py
CET/CFG-aware control-flow hijackT1203CWE-1419references/stack-rop-mitigations.mdscripts/rop_autochain.py
tcache/fastbin poisoning + safe-linkingT1203CWE-416references/heap-glibc-fsop.mdscripts/safe_linking.py
House of Botcake / Einherjar / Apple2T1203CWE-415references/heap-glibc-fsop.mdscripts/heap_fsop.py
FSOP (stdout leak, House of Apple 2)T1203CWE-787references/heap-glibc-fsop.mdscripts/heap_fsop.py
Format string leak + arbitrary writeT1203CWE-134references/format-string-leaks.mdscripts/fmtstr_leak.py
V8 type confusion -> addrof/fakeobjT1203CWE-843references/browser-jit-uaf.mdscripts/v8_primitives.js
V8 Sandbox escape (WASM jump table)T1203CWE-843references/browser-jit-uaf.mdscripts/v8_primitives.js
UAF heap-spray reclaimT1203CWE-416references/browser-jit-uaf.mdscripts/v8_primitives.js
Linux kernel UAF -> cross-cacheT1068CWE-416references/kernel-exploitation.mdscripts/kernel_lpe_skeleton.c
Dirty Pagetable / PagedirectoryT1068CWE-416references/kernel-exploitation.mdscripts/kernel_lpe_skeleton.c
msg_msg infoleak / sprayT1068CWE-125references/kernel-exploitation.mdscripts/kernel_lpe_skeleton.c
Windows PreviousMode / I/O Ring R/WT1068CWE-787references/kernel-exploitation.mdscripts/kernel_lpe_skeleton.c
Empirical mitigation matrix (build witness under N profiles)T1203CWE-693references/exploit-feasibility.mdscripts/feasibility_profile.py
Cached context + blocked-technique gate for /exploitT1203CWE-693references/exploit-feasibility.mdscripts/exploit_context.py

Quick Start

bash
# 0. Fingerprint target + libc (pin every version)
file ./target; pwn checksec ./target
strings -a libc.so.6 | grep -m1 'release version'   # exact glibc build
patchelf --set-interpreter ./ld.so --replace-needed libc.so.6 ./libc.so.6 ./target

# 1. Crash + offset (cyclic) — see scripts/offset_finder.py
python3 scripts/offset_finder.py ./target            # auto pattern_create/offset

# 2. Gadgets + one_gadget
ROPgadget --binary ./libc.so.6 > gadgets.txt
ropper -f ./libc.so.6 --search 'pop rdi; ret'
one_gadget ./libc.so.6

# 3. Build chain (leak -> base -> system/execve) — scripts/rop_autochain.py
python3 scripts/rop_autochain.py ./target ./libc.so.6 --leak puts --remote host:port

# 4. Heap targets: poison fd with safe-linking math, FSOP for the endgame
python3 scripts/safe_linking.py --chunk 0x55...000 --target 0x7f...   # encrypt fd
python3 scripts/heap_fsop.py --libc ./libc.so.6 --mode apple2         # FSOP payload

# 5. Verify reliability before delivery
for i in $(seq 1 50); do python3 exploit.py >/dev/null 2>&1 && echo ok; done | wc -l

Cache the target context once. Steps 0–2 (file/checksec/libc build, gadget table, one_gadget) describe the target, not a single attempt — compute them once and reuse them across every PoC iteration. Re-running recon on each attempt wastes budget and pollutes telemetry; an autopilot loop should treat the fingerprint + gadget set as cached input, not a per-iteration step. A future empirical feasibility profile (raptor-adoption PR-3) will rebuild the crash witness under several mitigation profiles and emit a machine-readable map of which techniques the target actually permits — the PoC is then forbidden from using a technique that map marks blocked. Until it lands: record the checksec/mitigation state explicitly and do not claim a technique the target's protections rule out.

OPSEC & Detection (summary)

TechniqueTelemetry/IOCDetection (Sigma/EDR)OPSEC note
ROP/ret2libcStack exec faults, abnormal execve("/bin/sh") child of network daemonEDR: child shell from listener; auditd execve of /bin/sh w/ empty argvUse in-memory ORW (open/read/write flag) instead of shell to avoid execve IOC
Heap/FSOPglibc *** stack smashing ***/malloc(): ... aborts in logs; SIGABRT crash loopsSigma: repeated SIGABRT/SIGSEGV from same PID; coredump burstsDisable coredumps (prctl(PR_SET_DUMPABLE,0)); tune spray to avoid abort()s
Format string%n/%p strings in request/argv logs; segfault on bad writeWAF/Sigma on %n,%[0-9]+\$n in inputsPre-stage write target; minimize % count, avoid huge field widths
V8 type confusionRenderer crash dumps, chrome_crashpad, GPU/renderer restartsCrashpad telemetry; EDR on renderer spawning unexpected processesKeep corruption inside cage; clean up sprayed arrays; avoid renderer crash on failure
Kernel LPEdmesg oops/RIP, KASAN splats, apparmor/audit LPE child = rootSigma: process gaining uid=0 w/o setuid path; EDR kernel-callbackFileless (no SUID drop); restore corrupted state; clear dmesg only if authorized

Deep Dives

  • references/stack-rop-mitigations.md — Stack overflow, ret2libc/ROP, ret2csu, SROP, stack pivots, ret2dlresolve; defeating ASLR/PIE/NX/canary/RELRO and CET shadow stack / CFG-aware constraints. Backed by offset_finder.py, rop_autochain.py.
  • references/heap-glibc-fsop.md — glibc 2.35-2.40 internals, tcache/fastbin poisoning under safe-linking, House of Botcake/Einherjar/Apple 2/Tangerine, stdout FSOP leak, post-hook-removal endgames. Backed by safe_linking.py, heap_fsop.py.
  • references/format-string-leaks.md — Read/write mechanics, stack-arg indexing, %n arbitrary write, PIE/libc/canary leaks, fmtstr automation and one-shot GOT/exit-handler overwrite. Backed by fmtstr_leak.py.
  • references/browser-jit-uaf.md — V8 element-kind confusion, addrof/fakeobj, arbitrary R/W under pointer compression, 2024-2025 Maglev/TurboFan CVEs, V8 Sandbox escape via WASM jump table, generic UAF reclaim. Backed by v8_primitives.js.
  • references/kernel-exploitation.md — Linux UAF/cross-cache, Dirty Pagetable/Pagedirectory (CVE-2024-1086), msg_msg leak/spray, SLUBStick; Windows pool spray, PreviousMode + I/O Ring R/W, CLFS/AFD CVEs. Backed by kernel_lpe_skeleton.c.
  • references/exploit-feasibility.md — empirical mitigation matrix: rebuild the crash witness under permissive/distro/hardened/asan profiles, record which still fire, derive the blocked-technique map; /exploit is forbidden a technique the map marks blocked. Backed by feasibility_profile.py (build/replay, Linux/devcontainer) + exploit_context.py (cached checksec/libc + the assert_allowed gate). Pairs with reverse-engineering/references/rr-time-travel.md + coverage-reachability.md.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Exploit Development AI skill do?

Use when turning a memory-corruption bug into a working PoC — stack/ROP, glibc heap & FSOP, format strings, browser/JIT type confusion & UAF, Linux/Windows kernel LPE against ASLR/DEP/CFG/CET/V8-Sandbox

Why use Exploit Development on TypingMind?

Because you install it once and use it with any model. Exploit Development is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Exploit Development in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hypnguyen1209/offensive-claude/tree/main/skills/exploit-development. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Exploit Development?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Exploit Development?

As many as you like. As long as a model supports skills, you can use Exploit Development with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Exploit Development AI skill free?

Yes. It is published on GitHub by hypnguyen1209 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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