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 trilwu/secskills --skill analyzing-binariesgit clone --depth 1 https://github.com/trilwu/secskillsWrote 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/trilwu/secskills/analyzing-binaries)<a href="https://agentmods.dev/skills/trilwu/secskills/analyzing-binaries"><img src="https://agentmods.dev/badge/skills/trilwu/secskills/analyzing-binaries/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/trilwu/secskills/analyzing-binaries"><img src="https://agentmods.dev/badge/skills/trilwu/secskills/analyzing-binaries.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Prompt Injection · line 233 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00068 | $0.02953 |
| Opus 5 | $0.00034 | $0.01477 |
| Sonnet 5 | $0.00014 | $0.00591 |
| Haiku 4.5 | $0.00007 | $0.00295 |
Grade A, and why
analyzing-binaries 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- analyzing-binaries — 86% identical, 26 lines differ
How it starts
The opening of the file, as written. The whole thing — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyzing Binaries
Reverse engineering is hypothesis testing against a program you cannot read. The cost of the job is dominated by how much code you look at, so the whole discipline is about narrowing: triage first, find the interesting few percent, then read that carefully.
When to Use
- Understanding what an unknown or undocumented executable does
- Recovering an algorithm, file format, or wire protocol from a binary
- Locating a vulnerability in a closed-source target
- Firmware analysis for embedded and IoT devices
- Reversing challenges in CTFs
When NOT to Use
- Live malware with intent to detonate — use
analyzing-malware, which covers containment and safe detonation. Come back here for the disassembly. - A raw shellcode blob with no headers (position-independent payload,
stager, egg-hunter) — use
analyzing-shellcode - Source is available — use
auditing-code-for-vulnerabilities - Android/iOS app assessment as a whole — use
testing-mobile-applications; use this skill for the native.so/Mach-O components inside it - A framework runtime rather than a plain binary — the toolchain is
specific and generic RE will not get there:
reversing-flutter-appsforlibapp.so/Dart snapshots,reversing-unity-il2cppforlibil2cpp.soplusglobal-metadata.dat,reversing-react-native-appsfor Hermes bytecode - A language runtime with its own symbol recovery —
analyzing-go-binaries(pclntabsurvives stripping),analyzing-rust-binaries(panic strings leak source paths),analyzing-dotnet-assemblies(IL decompiles to C#). Reaching for generic RE on these wastes most of the effort - A packed or protected executable — use
unpacking-protected-binariesfirst; there is nothing to disassemble until it is dumped - A whole firmware image to extract before any RE — use
analyzing-firmware-imagesforbinwalk, filesystem carving, and cross-architecture emulation; return here for an individual binary inside it
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 · 259 lines · 68 tokens per session scan A 0a84cdf6094a
analyzing-binaries is a skill published in the GitHub repository trilwu/secskills (137 stars, last pushed 4d ago), licensed MIT. It adds 68 tokens to every session and 2,953 once invoked, about $0.0003 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 2026-08-30.
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