Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add ogrodev/fsociety/plugin install romeroWrote 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/pe-analysis)<a href="https://agentmods.dev/skills/ogrodev/fsociety/pe-analysis"><img src="https://agentmods.dev/badge/skills/ogrodev/fsociety/pe-analysis/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/ogrodev/fsociety/pe-analysis"><img src="https://agentmods.dev/badge/skills/ogrodev/fsociety/pe-analysis.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 | $0.00401 | $0.03996 |
| Opus 5.5 | $0.00160 | $0.01598 |
| Sonnet 5.5 | $0.00080 | $0.00799 |
| Haiku 4.5 | $0.00040 | $0.00400 |
Grade A, and why
pe-analysis 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 387 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PE File Analysis
Portable Executable analysis is the foundation of Windows binary reverse engineering. Every .exe, .dll, .sys, .ocx, and .scr on Windows follows the PE format. Master PE structure and you can triage unknown binaries in minutes -- determine if they are packed, what they do, what anomalies they exhibit, and whether they warrant deeper analysis.
Triage Workflow
Follow this sequence when analyzing an unknown PE file. Each step builds on the previous one.
Step 1 — Compute Hashes and Basic Identification
Hash the binary first. Check hashes against known databases before spending time on manual analysis.
# SHA256 + MD5 + file type
node ${CLAUDE_PLUGIN_ROOT}/scripts/binary-hasher.js hash <binary>
file <binary>
# Check analysis database for prior work
node ${CLAUDE_PLUGIN_ROOT}/scripts/analysis-tracker.js check <sha256> pe-analysis
Record the hash immediately. Every subsequent finding references this hash.
Step 2 — Header Analysis
Extract PE headers to determine architecture, compile time, entry point, and security features.
# Full header dump with radare2
r2 -qc 'iH' <binary>
r2 -qc 'iI' <binary>
import pefile, time
pe = pefile.PE('<binary>')
# Compile timestamp
ts = pe.FILE_HEADER.TimeDateStamp
print(f"Compile time: {time.strftime('%Y-%m-%d %H:%M:%S', time.gmtime(ts))} UTC")
print(f"Machine: {hex(pe.FILE_HEADER.Machine)}")
print(f"Entry point: {hex(pe.OPTIONAL_HEADER.AddressOfEntryPoint)}")
print(f"Image base: {hex(pe.OPTIONAL_HEADER.ImageBase)}")
print(f"Subsystem: {pe.OPTIONAL_HEADER.Subsystem}")
# Security features
flags = pe.OPTIONAL_HEADER.DllCharacteristics
print(f"ASLR: {bool(flags & 0x40)}, DEP: {bool(flags & 0x100)}, CFG: {bool(flags & 0x4000)}")
print(f"No SEH: {bool(flags & 0x400)}, Force integrity: {bool(flags & 0x80)}")
Check for anomalies: future timestamps, epoch zero, entry point outside .text, missing ASLR/DEP.
See references/pe-headers.md for complete field reference.
What ships with it
6 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.
- 1mo ago First seen · 387 lines · 401 tokens per session scan A fc39881dec7b
pe-analysis is a skill published in the GitHub repository ogrodev/fsociety (20 stars, last pushed 7mo ago), licensed MIT. It adds 401 tokens to every session and 3,996 once invoked, about $0.0016 per session on Opus 5.5. 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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