pe-analysis

A workflow for examining Windows executable files such as EXE programs, DLL libraries, and SYS drivers. It checks file details, internal structure, and signs that a file may be unusual or protected from inspection.

In plain words
What is it for?
Use it to calculate file hashes, identify the file type and architecture, inspect headers, and record findings for later analysis.
Why use it?
It provides an organized first review of an unknown Windows binary before deeper reverse engineering.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/ogrodev/fsociety/pe-analysis
Any agent
npx skills add ogrodev/fsociety --skill pe-analysis
Clone the repo
git clone --depth 1 https://github.com/ogrodev/fsociety

Made for: Claude Code, Codex.

Per session 401 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,996 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00401 $0.03996
Opus 5 $0.00200 $0.01998
Sonnet 5 $0.00080 $0.00799
Haiku 4.5 $0.00040 $0.00400

Measured 2d ago against content hash fc39881dec7b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 2d 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.

romero/skills/pe-analysis/SKILL.md · 387 lines

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.

Read the full file on GitHub · 387 lines

Files

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.

Changes

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.

  1. 2d ago First seen · 387 lines · 401 tokens per session scan A fc39881dec7b

Subscribe to this mod's changes

pe-analysis is a skill published in the GitHub repository ogrodev/fsociety (20 stars, last pushed 5mo ago), licensed MIT. It adds 401 tokens to every session and 3,996 once invoked, about $0.0020 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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