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/meltedinhex/analyst-ai-pack/reverse-engineering-shellcodenpx skills add meltedinhex/analyst-ai-pack --skill reverse-engineering-shellcodegit 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/reverse-engineering-shellcode)<a href="https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/reverse-engineering-shellcode"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/reverse-engineering-shellcode.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 | $0.00068 | $0.00869 |
| Opus 5 | $0.00034 | $0.00434 |
| Sonnet 5 | $0.00014 | $0.00174 |
| Haiku 4.5 | $0.00007 | $0.00087 |
Grade A, and why
reverse-engineering-shellcode 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 yesterday.
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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reverse Engineering Shellcode
When to Use
- You extracted a raw code blob (from a document, exploit, injected memory region, or beacon) with no PE/ELF headers.
- You need to determine the architecture, recover the API-resolution method, and understand what the shellcode does.
- You want to emulate the shellcode safely to recover staged payloads or C2.
Do not use a file-format parser on shellcode — there is no header. Treat it as a flat byte stream at a known base and disassemble/emulate.
Prerequisites
- Capstone (
pip install capstone) for disassembly; Unicorn (pip install unicorn) for emulation. - Knowledge of the likely architecture/bitness (x86 vs x64) and calling context.
Workflow
Step 1: Determine architecture and entry
Try disassembling as x86 and x64; the one that yields coherent instructions (and a sane prologue) is correct. Shellcode usually starts executing at offset 0.
python scripts/analyst.py disasm shellcode.bin --arch x64
Step 2: Recognize API resolution
Windows shellcode typically walks the PEB to find kernel32, then resolves exports by hash:
mov rax, gs:[60h] ; PEB (x64) / mov eax, fs:[30h] (x86)
... traverse Ldr -> InMemoryOrderModuleList
... hash export names, compare to embedded constants
Recovered hash constants feed the API-hash resolver (see the obfuscation skill).
Step 3: Identify the technique
Look for egg hunters (searching memory for a tag), socket setup (reverse/bind shell), or a
download-and-exec stager (WinINet/WinHTTP resolution then a URL).
Step 4: Emulate to recover behavior
Emulate with Unicorn, hooking memory and (optionally) faking API calls, to observe the control flow and extract strings/URLs the static view hides:
python scripts/analyst.py emulate shellcode.bin --arch x64 --base 0x140000000
Step 5: Extract IOCs and payload
Recover C2 URLs/hosts, embedded second stages, and the resolved API set for the report.
Validation
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.
- yesterday First seen · 109 lines · 68 tokens per session scan A 1f6803fc4f71
reverse-engineering-shellcode is a skill published in the GitHub repository meltedinhex/analyst-ai-pack (22 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 68 tokens to every session and 869 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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