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/2233admin/reverse-skill-evolver/malware-analysisnpx skills add 2233admin/reverse-skill-evolver --skill malware-analysisgit clone --depth 1 https://github.com/2233admin/reverse-skill-evolverWhat 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 | $0.00000 | $0.02070 |
| Opus 5 | $0.00000 | $0.01035 |
| Sonnet 5 | $0.00000 | $0.00414 |
| Haiku 4.5 | $0.00000 | $0.00207 |
Grade A, and why
malware-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 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 — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Malware Analysis
YARA / Sigma / 沙箱 / IOC 提取 / 反反分析 静态 + 动态 + 行为三合一
适用场景
- 恶意软件样本分析(PE/ELF/Mach-O/APK/脚本)
- YARA 规则编写与验证
- Sigma 行为检测规则生成
- 沙箱自动化分析编排
- IOC 提取与威胁情报
- 反分析技术检测与绕过
六阶段分析流程
Phase 1: 初步分诊
# 快速静态检测
file sample.exe # 文件类型
strings sample.exe | grep -i "http\|cmd\|powershell\|base64" # 快速 IOCs
rabin2 -zz sample.exe # 字符串提取 + 交叉引用
floss sample.exe # 去混淆字符串提取(FireEye)
# PE 头部分析
pecheck sample.exe # PE 结构验证
pescan sample.exe # 异常检测(节表、入口点)
diec sample.exe # Detect It Easy(壳/编译器识别)
# Hash 查询
sha256sum sample.exe
# → VirusTotal / MalwareBazaar / Triage 查询
Phase 2: 静态分析
反汇编/反编译:
□ IDA Pro / Ghidra: 深度反编译
□ radare2: CLI 快速分析
□ x64dbg: Windows GUI 调试器
重点分析区域:
□ 入口点(Entry Point)→ 初始化逻辑
□ 导入表 → API 用途推断(CreateRemoteThread=注入, CryptEncrypt=勒索)
□ 资源段 → 嵌入 Payload(.rsrc 节)
□ 字符串表 → URL/C2/文件路径/Base64 blob
□ TLS 回调 → 调试器启动前执行
Phase 3: 沙箱动态分析
自动化沙箱:
□ Joe Sandbox / ANY.RUN / Triage: 商业沙箱
□ CAPE Sandbox: 开源 + YARA 集成(推荐)
□ ASD Azul: 开源恶意软件分析平台(2026 新发布)
□ Cuckoo Sandbox: 经典开源(逐步被 CAPE 取代)
监控重点:
□ 进程创建: CreateProcess / ShellExecute
□ 文件操作: WriteFile → 勒索? DeleteFile → Wiper?
□ 注册表: Run/RunOnce 持久化
□ 网络: HTTP/DNS → C2 通信
□ 内存: VirtualAllocEx → 进程注入
□ 服务: CreateService → 持久化
Phase 4: YARA 规则编写
// 规则结构
rule MalwareFamily_Example {
meta:
description = "检测 Example 恶意软件家族"
author = "分析者"
date = "2026-05"
severity = "high"
hash = "d41d8cd98f00b204e9800998ecf8427e"
mitre_id = "T1055" // Process Injection
strings:
// 字符串匹配
$str1 = "C2_SERVER_URL" ascii wide
$str2 = "payload.dat" ascii
// 十六进制匹配
$hex1 = { 8B 45 ?? 50 FF 15 [4] 85 C0 }
// 操作码序列: mov eax, [ebp-?]; push eax; call [import]; test eax, eax
// 正则匹配
$re1 = /https?:\/\/[a-z0-9.-]+\/[a-z]{3,8}\.php/ ascii
condition:
// 组合条件
uint16(0) == 0x5A4D and // MZ 头
filesize < 500KB and
(2 of ($str*) or $hex1)
}
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 · 208 lines · 0 tokens per session scan A dd910d3000ad
malware-analysis is a skill published in the GitHub repository 2233admin/reverse-skill-evolver (13 stars, last pushed 21d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,070 tokens. 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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