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analyzing-cobaltstrike-malleable-c2-profiles 精选

Parse and analyze Cobalt Strike Malleable C2 profiles with dissect.cobaltstrike (profiles and beacon-payload configs) and pyMalleableC2 (AST parsing) to extract HTTP/DNS transforms, URIs, headers, sleep/jitter, and injection behavior, then generate network detection signatures. Use when reverse-engineering a captured malleable profile or building detections against Cobalt Strike Beacon traffic.

在 GitHub 打开

安装方式

cp -r skills/analyzing-cobaltstrike-malleable-c2-profiles ~/.claude/skills/analyzing-cobaltstrike-malleable-c2-profiles

把该 skill 目录放进客户端 skills 目录。不同客户端的目录可能不同,Claude Code 默认是 ~/.claude/skills/

整仓一次性获取:git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git

依赖与权限

  • 无需 API Key
  • 无需联网
  • 依赖外部命令:python pip
  • 以上为按正文与 frontmatter 自动推断的信号,仅供参考;安装前建议先阅读原文。

SKILL.md 正文

来源 mukul975/Anthropic-Cybersecurity-Skills@54a7988 · 许可 Apache-2.0 · 内容未修改

Analyzing CobaltStrike Malleable C2 Profiles

Overview

Cobalt Strike Malleable C2 profiles are domain-specific language scripts that customize how Beacon communicates with the team server, defining HTTP request/response transformations, sleep intervals, jitter values, user agents, URI paths, and process injection behavior. Threat actors use malleable profiles to disguise C2 traffic as legitimate services (Amazon, Google, Slack). Analyzing these profiles reveals network indicators for detection: URI patterns, HTTP headers, POST/GET transforms, DNS settings, and process injection techniques. The dissect.cobaltstrike library can parse both profile files and extract configurations from beacon payloads, while pyMalleableC2 provides AST-based parsing using Lark grammar for programmatic profile manipulation and validation.

When to Use

  • When investigating security incidents that require analyzing cobaltstrike malleable c2 profiles
  • When building detection rules or threat hunting queries for this domain
  • When SOC analysts need structured procedures for this analysis type
  • When validating security monitoring coverage for related attack techniques

Prerequisites

  • Python 3.9+ with dissect.cobaltstrike and/or pyMalleableC2
  • Sample Malleable C2 profiles (available from public repositories)
  • Understanding of HTTP protocol and Cobalt Strike beacon communication model
  • Network monitoring tools (Suricata/Snort) for signature deployment
  • PCAP analysis tools for traffic validation

Steps

  1. Install libraries: pip install dissect.cobaltstrike or pip install pyMalleableC2
  2. Parse profile with C2Profile.from_path("profile.profile")
  3. Extract HTTP GET/POST block configurations (URIs, headers, parameters)
  4. Identify user agent strings and spoof targets
  5. Extract sleep time, jitter percentage, and DNS beacon settings
  6. Analyze process injection settings (spawn-to, allocation technique)
  7. Generate Suricata/Snort signatures from extracted network indicators
  8. Compare profile against known threat actor profile collections
  9. Extract staging URIs and payload delivery mechanisms
  10. Produce detection report with IOCs and recommended network signatures

Expected Output

A JSON report containing extracted C2 URIs, HTTP headers, user agents, sleep/jitter settings, process injection config, spawned process paths, DNS settings, and generated Suricata-compatible detection rules.

质量与来源

所属仓库
mukul975/Anthropic-Cybersecurity-Skills
仓库星标
3.4 万
最近更新
1 个月前
采集时间
今天
commit
54a798831d22
内容指纹
sha256:2fe22f7360029cf
文件路径
skills/analyzing-cobaltstrike-malleable-c2-profiles/SKILL.md

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