Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ShulkwiSEC/bb-huge --skill format-string-exploitationgit clone --depth 1 https://github.com/ShulkwiSEC/bb-hugeWrote 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.
[](https://agentmods.dev/skills/shulkwisec/bb-huge/format-string-exploitation)<a href="https://agentmods.dev/skills/shulkwisec/bb-huge/format-string-exploitation"><img src="https://agentmods.dev/badge/skills/shulkwisec/bb-huge/format-string-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.
<a href="https://agentmods.dev/skills/shulkwisec/bb-huge/format-string-exploitation"><img src="https://agentmods.dev/badge/skills/shulkwisec/bb-huge/format-string-exploitation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00058 | $0.03110 |
| Opus 5 | $0.00029 | $0.01555 |
| Sonnet 5 | $0.00012 | $0.00622 |
| Haiku 4.5 | $0.00006 | $0.00311 |
Grade A, and why
format-string-exploitation scanned grade A with 0 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 7d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to format-string-exploitation — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 313 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SKILL: Format String Exploitation — Expert Attack Playbook
AI LOAD INSTRUCTION: Expert format string techniques. Covers stack reading, arbitrary write via %n, GOT overwrite, __malloc_hook overwrite, pointer chain exploitation, blind format string, FORTIFY_SOURCE bypass, 64-bit null byte handling, and pwntools automation. Distilled from ctf-wiki fmtstr, CTF patterns, and real-world scenarios. Base models often miscalculate positional parameter offsets or forget 64-bit address placement after format string.
0. RELATED ROUTING
- stack-overflow-and-rop — combine format string leak with stack overflow for full exploit
- binary-protection-bypass — format string is the primary canary/PIE/ASLR leak method
- arbitrary-write-to-rce — convert format string write primitive to code execution targets
- heap-exploitation — heap address leak via format string for heap exploitation
1. VULNERABILITY IDENTIFICATION
Vulnerable Pattern
printf(user_input); // VULNERABLE: user controls format string
fprintf(fp, user_input); // VULNERABLE
sprintf(buf, user_input); // VULNERABLE
snprintf(buf, sz, user_input); // VULNERABLE
printf("%s", user_input); // SAFE: format string is fixed
Quick Test
Input: AAAA%p%p%p%p%p%p%p%p
If output shows stack values (hex addresses): format string confirmed
Look for 0x4141414141414141 in output to find your input offset
2. READING MEMORY
Stack Leak (%p)
| Format | Action | Use |
|---|---|---|
%p |
Print next stack value as pointer | Sequential stack dump |
%N$p |
Print N-th parameter as pointer | Direct positional access |
%N$lx |
Same as %p but explicit hex (64-bit) | Portable |
%N$s |
Dereference N-th parameter as string pointer | Read memory at pointer value |
Finding Your Input Offset
# Send: AAAAAAAA.%p.%p.%p.%p.%p.%p.%p.%p.%p.%p
# Output: AAAAAAAA.0x7ffd12340000.0x0.(nil).0x7f1234567890.0x4141414141414141...
# ↑ offset = 6 (example)
# Or automated:
for i in range(1, 30):
io.sendline(f'AAAA%{i}$p')
if '0x41414141' in io.recvline():
print(f'Offset = {i}')
break
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.
- 7d ago First seen · 313 lines · 58 tokens per session scan A 62893048bdbf
format-string-exploitation is a skill published in the GitHub repository ShulkwiSEC/bb-huge (22 stars, last pushed 2mo ago), licensed MIT. It adds 58 tokens to every session and 3,110 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to format-string-exploitation, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
skill-debug
Debug a reproducible symptom with a bounded feedback loop and original-scenario verification.
debug
Use when something is broken — a failing or flaky test, crash, wrong result or regression — and the root cause must be reproduced and proven before any fix. On-demand; callable mid-implement. NOT a feature to spec or build (that is specify/implement), NOT the lint/test gate (that is verify), NOT adversarial diff…
pwn-ai-agent-reflect
Drive PWN::AI::Agent::Reflect from pwneval.
pwn-ai-agent-transparentbrowser
Drive PWN::AI::Agent::TransparentBrowser from pwneval.
continuum-observability
Trace agent runs with Langfuse, decorate functions with @observe, collect latency/token/error metrics, and report errors. Invoke when the user asks about "see what the LLM was prompted with", "Langfuse traces", "track latency", "metrics dashboard", "error reporting", or "instrument my function".
pwn-ai-agent-tools-debuglane
Drive PWN::Ai::Agent::Tools::DebugLane from pwneval.