Agent Skillszhaoxuya520/reverse-skill › competition-malware-config

competition-malware-config

GitHub

作为沙箱编排器的下游技能,用于CTF环境中恢复恶意软件配置、解码C2信标参数及IOC。支持分阶段载荷边界识别、加密链重构及行为关联分析,需在沙箱假设建立后调用。

CTF-Sandbox-Orchestrator/competition-malware-config/SKILL.md zhaoxuya520/reverse-skill

Trigger Scenarios

用户请求恢复恶意软件配置 需要解码C2或信标字段 要求解压分阶段载荷 提取机器人或活动ID 在沙箱环境下关联配置与协议行为

Install

npx skills add zhaoxuya520/reverse-skill --skill competition-malware-config -g -y
More Options

Non-standard path

npx skills add https://github.com/zhaoxuya520/reverse-skill/tree/main/CTF-Sandbox-Orchestrator/competition-malware-config -g -y

Use without installing

npx skills use zhaoxuya520/reverse-skill@competition-malware-config

指定 Agent (Claude Code)

npx skills add zhaoxuya520/reverse-skill --skill competition-malware-config -a claude-code -g -y

安装 repo 全部 skill

npx skills add zhaoxuya520/reverse-skill --all -g -y

预览 repo 内 skill

npx skills add zhaoxuya520/reverse-skill --list

SKILL.md

Frontmatter
{
    "name": "competition-malware-config",
    "description": "Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for malware configuration recovery, staged payload boundaries, beacon parameter extraction, and IOC decoding. Use when the user asks to recover a malware config, decode C2 or beacon fields, unpack staged payloads, extract bot or campaign IDs, or tie recovered config to observed protocol behavior under sandbox assumptions. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here."
}

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

  1. Preserve the original sample before unpacking or patching.
  2. Separate loader, payload, config blob, and post-decode behavior.
  3. Rank candidate config blobs by entropy, field shape, nearby strings, and decode helpers.
  4. Record the exact transform chain for each recovered field.
  5. 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.md for the config-hunting checklist, staged-sample checklist, and evidence packaging rules.

What To Preserve

  • Original artifact, unpacked layer, dumped stage, and parsed config as separate artifacts
  • Offsets, hashes, decode helpers, keys, masks, and field names
  • The branch or protocol step each recovered field actually influences

Version History

  • 1bec1f2 Current 2026-07-05 18:45

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Metadata

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Version
1bec1f2
Hash
e8ece81a
Indexed
2026-07-05 18:45

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