Reverse Skill is a routing package for AI coding agents that selects appropriate reverse-engineering, penetration-testing, and security-research methods and tools for a given target. It is used for tasks involving APKs, binaries, frontend JavaScript, packet captures, CTF challenges, and authorized penetration testing. Its catalogue add-ons provide the skills and instructions that guide these workflows.
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 zhaoxuya520/reverse-skill --skill competition-malware-configgit clone --depth 1 https://github.com/zhaoxuya520/reverse-skillWrote 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/zhaoxuya520/reverse-skill/competition-malware-config)<a href="https://agentmods.dev/skills/zhaoxuya520/reverse-skill/competition-malware-config"><img src="https://agentmods.dev/badge/skills/zhaoxuya520/reverse-skill/competition-malware-config/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/zhaoxuya520/reverse-skill/competition-malware-config"><img src="https://agentmods.dev/badge/skills/zhaoxuya520/reverse-skill/competition-malware-config.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00101 | $0.00574 |
| Opus 5 | $0.00051 | $0.00287 |
| Sonnet 5 | $0.00020 | $0.00115 |
| Haiku 4.5 | $0.00010 | $0.00057 |
Grade A, and why
competition-malware-config 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 12d 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.
Copies of this mod
4 near-identical copies found in the catalogue:
- competition-malware-config — 100% identical, 0 lines differ
- competition-malware-config — 100% identical, 0 lines differ
- competition-malware-config — 100% identical, 0 lines differ
- competition-malware-config — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competition Malware Config
Use this skill only as a downstream specialization after $ctf-sandbox-orchestrator is already active and has established sandbox assumptions, node ownership, and evidence priorities. If that has not happened yet, return to $ctf-sandbox-orchestrator first.
Use this skill when the decisive value is not just "what the sample does," but which config fields, stages, or network parameters the sample hides and when they become plaintext.
Reply in Simplified Chinese unless the user explicitly requests English.
Quick Start
- Preserve the original sample before unpacking or patching.
- Separate loader, payload, config blob, and post-decode behavior.
- Rank candidate config blobs by entropy, field shape, nearby strings, and decode helpers.
- Record the exact transform chain for each recovered field.
- Reproduce the decoded config or beacon parameters from the smallest possible path.
Workflow
1. Find The Config Boundary
- Inspect sections, resources, embedded archives, strings, imports, and decode helpers.
- Identify where config is stored: resource, overlay, encrypted blob, registry seed, network bootstrap, or stage2 memory.
- Keep one note of when each value becomes plaintext.
2. Reconstruct The Decode Chain
- Recover the chain in order: container -> compression -> encoding -> xor/substitution -> crypto -> parse.
- Group all config fields from the same chain together instead of treating them as unrelated clues.
- Preserve hashes, offsets, keys, IVs, masks, and parsed fields in one compact evidence block.
3. Tie Config To Behavior
- Show which field affects which branch: beacon path, mutex, wallet, bot id, campaign, tasking route, persistence name, or process target.
- Correlate decoded config with PCAPs, process trees, or stage2 strings when possible.
Read This Reference
- Load
references/malware-config.mdfor the config-hunting checklist, staged-sample checklist, and evidence packaging rules.
What To Preserve
What ships with it
2 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.
- 12d ago First seen · 50 lines · 101 tokens per session scan A e8ece81ac60b
competition-malware-config is a skill published in the GitHub repository zhaoxuya520/reverse-skill (35,595 stars, last pushed 8d ago), licensed MIT. It adds 101 tokens to every session and 574 once invoked, about $0.0005 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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