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 0dayInc/pwn --skill ffigit clone --depth 1 https://github.com/0dayInc/pwnWrote 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/0dayinc/pwn/ffi)<a href="https://agentmods.dev/skills/0dayinc/pwn/ffi"><img src="https://agentmods.dev/badge/skills/0dayinc/pwn/ffi/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/0dayinc/pwn/ffi"><img src="https://agentmods.dev/badge/skills/0dayinc/pwn/ffi.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00016 | $0.00411 |
| Opus 5 | $0.00008 | $0.00205 |
| Sonnet 5 | $0.00003 | $0.00082 |
| Haiku 4.5 | $0.00002 | $0.00041 |
Grade A, and why
pwn-ffi 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 9d 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.
What it actually says
PWN::FFI
This file, using the autoload directive loads FFI modules into memory only when they're needed. For more information, see: http://www.rubyinside.com/ruby-techniques-revealed-autoload-1652.html Bindings under this namespace are thin — they attach functions from already-installed system shared objects (libliquid, libvolk, libfftw3f, librtlsdr, libhackrf, libSoapySDR) so PWN::SDR::Decoder::* can run MHz-rate DSP inner loops in native/SIMD code while Ruby stays in charge of orchestration. Nothing here shells out; nothing here compiles at gem install time. If a .so is missing the module still loads and .available? returns false so callers can fall back to pure Ruby.
When to use
Call PWN::FFI from pwn_eval when the task needs this module.
Do not reimplement it in shell.
Methodologies
Generated from pwn/ffi.rb. Prefer the public class methods below.
Class methods take (opts = {}) and read opts.
How to call
PWN::FFI.help
PWN::FFI.available(opts)
Public methods
availablebackendsauthorshelpavailable?
References
references/urls.md— URLs from source
Source
pwn/ffi.rb
Verification
PWN::FFI.respond_to?(:available) after the
module is loaded. Read the source for parameter names.
What ships with it
9 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.
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.
- 9d ago First seen · 54 lines · 16 tokens per session scan A 745ce07df1d2
pwn-ffi is a skill published in the GitHub repository 0dayInc/pwn (82 stars, last pushed yesterday), licensed MIT. It adds 16 tokens to every session and 411 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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