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 meltedinhex/analyst-ai-pack --skill performing-static-pe-analysisgit clone --depth 1 https://github.com/meltedinhex/analyst-ai-packWrote 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/meltedinhex/analyst-ai-pack/performing-static-pe-analysis)<a href="https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/performing-static-pe-analysis"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/performing-static-pe-analysis.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 5.1 | $0.00064 | $0.00860 |
| Opus 5 | $0.00032 | $0.00430 |
| Sonnet 5 | $0.00013 | $0.00172 |
| Haiku 4.5 | $0.00006 | $0.00086 |
Grade A, and why
performing-static-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 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.
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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performing Static PE Analysis
When to Use
- You have a Windows executable or DLL and need to infer its capabilities before (or instead of) detonation.
- You want to assess packing, suspicious imports, timestamps, and embedded resources.
- You are gathering features for YARA authoring or detection.
Do not use import tables alone to conclude behavior — packed samples hide imports until runtime. If imports are sparse and entropy is high, move to unpacking.
Prerequisites
pefile(pip install pefile) and optionallycapa/PEStudio for deeper capability ID.- The sample in neutralized form inside the lab.
Safety & Handling
- Static only: parse the file, never run it. Keep the neutralized extension.
Workflow
Step 1: Parse headers and metadata
python scripts/analyst.py analyze sample.bin
Note the compile timestamp (often forged), subsystem (GUI/console), machine type (x86/x64), and whether it is a DLL.
Step 2: Review sections and entropy
Per-section entropy reveals packing. A tiny .text plus a huge high-entropy section, or
non-standard section names (UPX0, .themida), indicate a packer:
.text entropy 6.4 (normal code)
UPX1 entropy 7.95 (packed)
Step 3: Classify imports
Group imported APIs into behavioral buckets:
Injection : VirtualAllocEx, WriteProcessMemory, CreateRemoteThread [T1055]
Network : InternetOpen, HttpSendRequest, WinHttpConnect [T1071]
Crypto : CryptEncrypt, CryptAcquireContext [T1486]
Persistence: RegSetValueEx, CreateService [T1547/T1543]
A sample importing only LoadLibrary/GetProcAddress is resolving APIs dynamically — a
packing/evasion tell.
Step 4: Inspect resources and strings
Look for embedded PEs in resources (droppers), config blobs, and notable strings (URLs, mutex names, paths).
Step 5: Check signing
Verify the Authenticode signature: unsigned, self-signed, or revoked certificates are suspicious for software claiming to be legitimate.
What ships with it
3 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 · 115 lines · 64 tokens per session scan A a99440482b3c
performing-static-pe-analysis is a skill published in the GitHub repository meltedinhex/analyst-ai-pack (22 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 64 tokens to every session and 860 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 2026-09-03.
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