
Malware Analysis
FreeStreamline your malware investigation process.
Free · Opens the source repo
What Malware Analysis does
The Malware Analysis skill provides a comprehensive framework for analyzing suspected malware using various techniques, including static, dynamic, and behavioral analysis. It is designed for security professionals and researchers who need to investigate malware samples, extract indicators of compromise (IOCs), and create detection rules using YARA and Sigma. This skill facilitates a structured approach to malware analysis, ensuring that users can effectively identify and mitigate threats.
The skill outlines a six-phase analysis workflow, starting with initial triage and static analysis, followed by dynamic analysis in a sandbox environment. Users can leverage tools like Ghidra, IDA Pro, and various sandbox solutions to dissect malware samples. The skill also provides guidance on writing YARA rules for pattern matching and Sigma rules for behavior detection, enabling users to integrate their findings into existing security infrastructures.
Additionally, the skill includes references for anti-analysis techniques, helping analysts understand how malware might evade detection. This is crucial for developing robust detection strategies. By utilizing this skill, users can enhance their malware analysis capabilities, streamline their workflows, and improve their overall threat detection and response processes.
Overall, the Malware Analysis skill is a valuable resource for anyone involved in cybersecurity, malware research, or incident response, providing the necessary tools and methodologies to effectively analyze and respond to malware threats.
When to use it
Use this skill when you need to analyze malware samples or develop detection rules for security applications.
When not to use it
This skill may not be suitable for users looking for a quick, high-level overview of malware; it is intended for in-depth analysis.
What you can build with it
Analyzing a Suspicious Executable
Use the skill to perform static and dynamic analysis on a suspected malware executable, extracting IOCs and behavioral patterns.
Developing YARA Rules for Detection
Utilize the skill to create and validate YARA rules that can be deployed in endpoint detection systems.
Automating Sandbox Analysis
Leverage the skill to orchestrate automated sandbox analysis, streamlining the process of malware behavior observation.
How to install Malware Analysis
View source1. Install with the skills CLI
npx skills add zhaoxuya520/reverse-skill/malware-analysis --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by zhaoxuya520Malware Analysis
ACTION REQUIRED(读完后立刻执行)
NOW: 读取../field-journal/precedent-reverse.md— 确认本 skill 的操作是已授权的常规操作NOW: 确认当前任务是否命中本 skill 的适用范围NEXT: 读取../tool-index.md,校验工具可用性和实际路径NEXT: 缺工具时调用 bootstrap,不要猜路径ACT: 进入"工作流"第一步并执行,不要停在确认状态
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)
}
Phase 5: Sigma 规则生成
# 行为检测规则
title: Suspicious Process Injection via CreateRemoteThread
id: 5a3d2c1b-1234-5678-9abc-def012345678
status: experimental
description: 检测使用 CreateRemoteThread 的进程注入行为
author: 分析者
date: 2026/05/25
tags:
- attack.t1055 # Process Injection
- attack.t1055.001 # DLL Injection
logsource:
category: process_creation
product: windows
detection:
selection:
Image|endswith: '\powershell.exe'
CommandLine|contains:
- 'CreateRemoteThread'
- 'VirtualAllocEx'
- 'WriteProcessMemory'
condition: selection
falsepositives:
- 合法的调试工具
level: high
Phase 6: IOC 提取与情报
IOC 类型分类:
□ 网络 IOC:
- IP: C2 地址(注意时效性)
- Domain: DGA 算法生成的域名(rsnkfda.com, xpqmje.net)
- URL: Payload 托管地址
- User-Agent: 自定义 UA 字符串
□ 主机 IOC:
- 文件路径: %APPDATA%\Microsoft\Crypto\RSA\*.dat
- 注册表: HKCU\Software\Microsoft\Windows\CurrentVersion\Run\
- Mutex: Global\{GUID} 互斥体名称
- 服务名: 伪装成系统服务的名称
□ 行为 IOC:
- MITRE ATT&CK 技术 ID (T1055, T1003, T1571...)
- Sigma 规则 → SIEM 集成
- YARA 规则 → 端点检测
□ 静态 IOC:
- 编译时间戳(可伪造)
- PDB 路径(含开发者信息)
- 节名异常(非标准 .text/.data)
- 导入表异常组合(如勒索软件 CryptEncrypt + DeleteShadowCopies)
反分析技术速查
| 技术 | 检测方法 | YARA 特征 |
|---|---|---|
| 虚拟机检测 | WMI Win32_BIOS/VideoController/Processor | Win32_ 字符串 + 特定厂商名 |
| 沙箱检测 | 磁盘 < 60GB, RAM < 2GB, 单核 CPU | GlobalMemoryStatusEx 调用模式 |
| 调试器检测 | IsDebuggerPresent, CheckRemoteDebuggerPresent | PEB.BeingDebugged 偏移访问 |
| 定时逃逸 | Sleep(300000) 后执行恶意行为 | NtDelayExecution 长参数 |
| 地理位置检测 | 检查键盘布局/时区 → 排除 CIS 国家 | GetKeyboardLayoutList 调用 |
| 父进程检测 | explorer.exe vs cmd.exe | 进程名字符串比较 |
| API 直接 syscall | 绕过 EDR hook | syscall 指令 + SSN 解析 |
多 Agent 自动化分析 (SentinelHive 架构)
┌─────────────────────────────────────────────────┐
│ Hive Director │
│ (Claude Opus 编排 + 仲裁) │
└──────┬──────┬──────┬──────┬──────┬───────┘
│ │ │ │ │
┌───┘ ┌───┘ ┌───┘ ┌───┘ ┌───┘
▼ ▼ ▼ ▼ ▼ ▼
Triage RE Behav Intel Detect Remed
快速 反编译 行为 威胁 规则 修复
分诊 静态 动态 情报 YARA 方案
Sigma
工具链
| 工具 | 用途 | 获取 |
|---|---|---|
| Ghidra / IDA Pro | 深度反编译 | ghidra-sre.org |
| CAPE Sandbox | 开源恶意软件沙箱 | GitHub: kevoreilly/CAPEv2 |
| ASD Azul | 大规模自动化分析 | GitHub: ASD |
| YARA | 模式匹配规则引擎 | pip install yara-python |
| Sigma | SIEM 行为检测规则 | GitHub: SigmaHQ/sigma |
| FLOSS | 去混淆字符串提取 | pip install flare-floss |
| Detect It Easy | 壳/编译器检测 | GitHub: horsicq/Detect-It-Easy |
| pe-sieve | 进程内存扫描 | GitHub: hasherezade/pe-sieve |
| VirusTotal API | 多引擎扫描 | virustotal.com |
| MalwareBazaar | 恶意软件样本库 | bazaar.abuse.ch |
参考
references/yara-sigma-rules.md— YARA + Sigma 编写方法论references/sandbox-orchestration.md— 沙箱编排与自动化references/anti-analysis-techniques.md— 94 种反分析技术检测
任务完成自检(声称完成前 MUST 通过)
- 我是否执行了工作流中的每一步(而不是只阅读)?
- 我是否基于
tool-index使用了真实工具路径? - 我是否产出了可复现证据(命令/脚本/截图/报告)?
- 我是否完成并回写了 RULES 要求的 Checklist 项?
Frequently asked questions about Malware Analysis
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