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-custom-c2-protocolsnpx skills add meltedinhex/analyst-ai-pack --skill reverse-engineering-custom-c2-protocolsgit 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-custom-c2-protocols)<a href="https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/reverse-engineering-custom-c2-protocols"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/reverse-engineering-custom-c2-protocols.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 | $0.00070 | $0.00814 |
| Opus 5 | $0.00035 | $0.00407 |
| Sonnet 5 | $0.00014 | $0.00163 |
| Haiku 4.5 | $0.00007 | $0.00081 |
Grade A, and why
reverse-engineering-custom-c2-protocols 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.
How it starts
The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reverse Engineering Custom C2 Protocols
When to Use
- A sample uses a non-standard protocol (or a custom layer over HTTP/TCP) and you must decode its traffic.
- You need to recover message framing, the encryption/encoding scheme, and the command set.
- You want to build a standalone decoder or emulator to parse captured beacon traffic.
Do not use this for documented protocols handled by existing dissectors — use the protocol analyzer directly instead of reversing from scratch.
Prerequisites
- A disassembler/debugger and a network capture (PCAP) of the sample's traffic where possible.
- The crypto/obfuscation skills for recovering keys and encodings.
Workflow
Step 1: Locate the network routines
Find send/recv/WSASend/WinHTTP calls (or the framework wrappers) and the buffers they
operate on. These bracket the serialization and crypto.
Step 2: Recover framing
Trace how outbound buffers are built: magic bytes, length prefixes, sequence/ID fields, and type/opcode fields. Document the header layout.
[ magic(4) ][ len(4 LE) ][ opcode(1) ][ flags(1) ][ payload(len) ]
Step 3: Recover crypto/encoding
Identify the transform applied before send / after recv (XOR with embedded key, RC4, AES, base64). Recover keys from the binary or from the key-setup routine.
Step 4: Reconstruct the command set
Map opcodes to handlers (shell, download, upload, sleep/jitter, exit) by following the dispatch switch. Build a table of command → behavior.
Step 5: Build a decoder and validate
Implement a parser/decryptor and run it against captured traffic; confirm it yields coherent commands and recovers the beacon's config.
python scripts/analyst.py decode capture.bin --key 0x5a --magic 4d5a4331
Validation
- The decoder parses every message in a real capture without desync.
- Decrypted payloads are coherent (printable commands / structured config).
- The opcode table matches the dispatch logic observed in the binary.
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.
- 2d ago First seen · 99 lines · 70 tokens per session scan A 13f358110bba
reverse-engineering-custom-c2-protocols is a skill published in the GitHub repository meltedinhex/analyst-ai-pack (22 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 70 tokens to every session and 814 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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