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profiling-threat-actor-groups分析威胁行为者群体

Agent Skill

profiling-threat-actor-groups 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

216

周安装

9

GitHub Stars

5,933

下载量

72
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:profiling-threat-actor-groups(分析威胁行为者群体)
来源仓库:https://github.com/mukul975/anthropic-cybersecurity-skills
仓库路径:skills/profiling-threat-actor-groups
安装命令:
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill profiling-threat-actor-groups
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill profiling-threat-actor-groups

简介

profiling-threat-actor-groups 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。

  • 适用于网络安全威胁分析、攻击模式识别或安全事件调查等待分类任务。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限范围和联网能力。
  • 建议核实维护状态,避免触发不必要的文件读写或命令执行操作。
  • 可结合原始 README 进一步了解具体用法和功能边界。

SKILL.md

Profiling Threat Actor Groups

When to Use

Use this skill when:

  • Updating the organization's threat model with profiles of adversary groups recently observed targeting your sector
  • Preparing an executive briefing on APT groups that align with geopolitical events affecting your business
  • Enabling SOC analysts to understand attacker objectives and TTPs to improve detection tuning

Do not use this skill for real-time incident attribution — attribution during active incidents should be deprioritized in favor of containment. Profile refinement occurs post-incident.

Prerequisites

  • Access to MITRE ATT&CK Groups database (https://attack.mitre.org/groups/)
  • Commercial threat intelligence subscription (Mandiant Advantage, CrowdStrike Falcon Intelligence, or Recorded Future)
  • Sector-specific ISAC membership for targeted intelligence (FS-ISAC, H-ISAC, E-ISAC)
  • Structured profile template (see workflow below)

Workflow

Step 1: Identify Relevant Threat Actors

Cross-reference your organization's sector, geography, and technology stack against known adversary targeting patterns. Sources:

  • MITRE ATT&CK Groups: 130+ documented nation-state and criminal groups with TTP mappings
  • CrowdStrike Annual Threat Report: adversary naming by nation-state (BEAR=Russia, PANDA=China, KITTEN=Iran, CHOLLIMA=North Korea)
  • Mandiant M-Trends: annual report with sector-specific targeting statistics
  • CISA Known Exploited Vulnerabilities (KEV) catalog: identifies vulnerabilities actively exploited by specific threat actors

Shortlist 5–10 groups most likely to target your organization based on sector alignment and recent activity.

Step 2: Collect Profile Data

For each adversary, document across standard dimensions:

Identity: ATT&CK Group ID (e.g., G0016 for APT29), aliases (Cozy Bear, The Dukes, Midnight Blizzard), suspected nation-state sponsor

Motivations: Espionage, financial gain, disruption, intellectual property theft

Targeting: Sectors, geographies, organization sizes, technology targets (OT/IT, cloud, supply chain)

Capabilities: Custom malware (e.g., APT29's SUNBURST, MiniDuke), exploitation of 0-days vs. known CVEs, supply chain attack capability

Campaign History: Notable operations with dates (SolarWinds 2020, Exchange Server 2021, etc.)

TTPs by ATT&CK Phase: Document top 5 techniques per tactic phase

Step 3: Map TTPs to ATT&CK

Using mitreattack-python:

from mitreattack.stix20 import MitreAttackData

mitre = MitreAttackData("enterprise-attack.json")
apt29 = mitre.get_object_by_attack_id("G0016", "groups")
techniques = mitre.get_techniques_used_by_group(apt29)

profile = {}
for item in techniques:
    tech = item["object"]
    tid = tech["external_references"][0]["external_id"]
    tactic = [p["phase_name"] for p in tech.get("kill_chain_phases", [])]
    profile[tid] = {"name": tech["name"], "tactics": tactic}

Step 4: Assess Detection Coverage Against Profile

Compare the adversary's technique list against your detection coverage matrix (from ATT&CK Navigator layer). Identify:

  • Techniques used by this group where you have no detection (critical gaps)
  • Techniques where you have partial coverage (logging but no alerting)
  • Compensating controls where detection is not feasible (network segmentation as mitigation for lateral movement)

Step 5: Package Profile for Distribution

Structure the final profile for different audiences:

  • Executive summary (1 page): Who, motivation, recent campaigns, top risk to our organization, recommended priority actions
  • SOC analyst brief (3–5 pages): Full TTP list with detection status, IOC list, hunt hypotheses
  • Technical appendix: YARA rules, Sigma detections, STIX JSON object for TIP import

Classify TLP:AMBER for internal distribution; seek ISAC approval before external sharing.

Key Concepts

TermDefinition
APTAdvanced Persistent Threat — well-resourced, sophisticated adversary (typically nation-state or sophisticated criminal) conducting long-term targeted operations
TTPsTactics, Techniques, Procedures — behavioral fingerprint of an adversary group, more durable than IOCs which change frequently
AliasesThreat actors receive different names from different vendors (APT29 = Cozy Bear = The Dukes = Midnight Blizzard = YTTRIUM)
AttributionProcess of associating an attack with a specific threat actor; requires multiple independent corroborating data points and carries inherent uncertainty
ClusterA group of related intrusion activity that may or may not be attributable to a single actor; used when attribution is uncertain
Intrusion SetSTIX SDO type representing a grouped set of adversarial behaviors with common objectives, even if actor identity is unknown

Tools & Systems

  • MITRE ATT&CK Groups: Free, community-maintained database of 130+ documented adversary groups with referenced campaign reports
  • Mandiant Advantage Threat Intelligence: Commercial platform with detailed APT profiles, malware families, and campaign analysis
  • CrowdStrike Falcon Intelligence: Commercial feed with adversary-centric profiles and real-time attribution updates
  • Recorded Future Threat Intelligence: Combines OSINT, dark web, and technical intelligence for adversary profiling
  • OpenCTI: Graph-based visualization of threat actor relationships, tooling, and campaign linkages

Common Pitfalls

  • IOC-centric profiles: Building profiles around IP addresses and domains rather than TTPs means the profile becomes stale within weeks as infrastructure rotates.
  • Vendor alias confusion: Conflating two different threat actor groups due to shared malware or infrastructure leads to incorrect threat model assumptions.
  • Binary attribution: Treating attribution as certain when it is probabilistic. Always qualify attribution confidence level (Low/Medium/High).
  • Neglecting insider and criminal groups: Overemphasis on nation-state APTs while ignoring ransomware groups (Cl0p, LockBit, ALPHV) which represent higher probability threats for most organizations.
  • Profile staleness: Adversary TTPs evolve. Profiles not updated quarterly may miss technique changes, new malware, or targeting shifts.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

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能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

38.35%
按下载量换算28

Claude

28.75%
按下载量换算21

Cursor

20.76%
按下载量换算15

Gemini CLI

9.34%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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