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 agentmods add skills/ogrodev/fsociety/secret-extractionnpx skills add ogrodev/fsociety --skill secret-extractiongit clone --depth 1 https://github.com/ogrodev/fsocietyWrote 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/ogrodev/fsociety/secret-extraction)<a href="https://agentmods.dev/skills/ogrodev/fsociety/secret-extraction"><img src="https://agentmods.dev/badge/skills/ogrodev/fsociety/secret-extraction.svg" alt="Measured on agentmods" 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 | $0.00548 | $0.03177 |
| Opus 5 | $0.00274 | $0.01588 |
| Sonnet 5 | $0.00110 | $0.00635 |
| Haiku 4.5 | $0.00055 | $0.00318 |
Grade C, and why
secret-extraction scanned grade C with 1 finding 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 4d 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.
Harvests environment variableshighData exfiltration
Enumerating or grepping the environment for keys collects credentials unrelated to what the mod says it does.
This skill activates when the user mentions "extract secrets", "find credentials", How it starts
The opening of the file, as written. The whole thing — 303 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Secret & Credential Extraction
Extract hardcoded credentials, API keys, cryptographic material, certificates, configuration secrets, and sensitive data from compiled binaries. This skill covers the full pipeline: string extraction, pattern matching, entropy analysis, crypto identification, format-specific extraction, and anti-analysis bypass.
Why This Matters
Hardcoded secrets in binaries are among the highest-impact findings in both penetration testing and malware analysis. A single embedded AWS key grants cloud access. A hardcoded database password opens the entire backend. An extracted C2 encryption key lets you decrypt all traffic. Developers embed secrets assuming compilation hides them -- it does not.
Methodology Overview
Execute these phases in order. Each phase feeds the next.
Phase 1 — Triage and Hash
Before touching strings, identify what you have. File type determines extraction strategy.
file <binary>
sha256sum <binary>
node ${CLAUDE_PLUGIN_ROOT}/scripts/binary-hasher.js hash <binary>
Record the hash. Check if this binary was already analyzed:
node ${CLAUDE_PLUGIN_ROOT}/scripts/analysis-tracker.js check <sha256> string-extraction
Phase 2 — Static String Extraction
Extract all readable strings. Start broad, then filter.
# ASCII strings, 6+ chars (reduces noise vs default 4)
strings -a -n 6 <binary> > strings_ascii.txt
# UTF-16 LE (Windows wchar_t, most common for Windows binaries)
strings -a -n 6 -el <binary> > strings_utf16.txt
# Combine and deduplicate
cat strings_ascii.txt strings_utf16.txt | sort -u > strings_all.txt
Count and triage:
wc -l strings_all.txt
# < 500 lines: review manually
# 500-5000: filter with patterns below
# > 5000: use targeted extraction only
Phase 3 — Obfuscated String Recovery
FLOSS recovers strings that strings cannot see: stack-built strings, tight loops, and runtime-decoded strings. This is where the real secrets hide.
# Full analysis (slow but thorough)
floss <binary>
# Stack strings only (fast, catches char-by-char construction)
floss --only stack <binary>
# Decoded strings (emulation-based, slowest, highest value)
floss --only decoded <binary>
# JSON output for automated processing
floss -j <binary> > floss_output.json
What ships with it
5 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.
- 4d ago First seen · 303 lines · 548 tokens per session scan C 959605970cbc
secret-extraction is a skill published in the GitHub repository ogrodev/fsociety (20 stars, last pushed 5mo ago), licensed MIT. It adds 548 tokens to every session and 3,177 once invoked, about $0.0027 per session on Opus 5. A static security scan graded it C with 1 finding (harvests environment variables). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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