external/anthropic-cybersecurity-skills/skills/profiling-threat-actor-groups/SKILL.md
Develops comprehensive threat actor profiles for APT groups, criminal organizations, and hacktivist collectives by aggregating TTP documentation, historical campaign data, tooling fingerprints, and attribution indicators from multiple intelligence sources. Use when briefing executives on sector-specific threats, updating threat model assumptions, or prioritizing defensive controls against specific adversaries. Activates for requests involving MITRE ATT&CK Groups, Mandiant APT profiles, CrowdStrike adversary naming, or sector-specific threat briefings.
npx skillsauth add seikaikyo/dash-skills profiling-threat-actor-groupsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Use this skill when:
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.
Cross-reference your organization's sector, geography, and technology stack against known adversary targeting patterns. Sources:
Shortlist 5–10 groups most likely to target your organization based on sector alignment and recent activity.
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
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}
Compare the adversary's technique list against your detection coverage matrix (from ATT&CK Navigator layer). Identify:
Structure the final profile for different audiences:
Classify TLP:AMBER for internal distribution; seek ISAC approval before external sharing.
| Term | Definition | |------|-----------| | APT | Advanced Persistent Threat — well-resourced, sophisticated adversary (typically nation-state or sophisticated criminal) conducting long-term targeted operations | | TTPs | Tactics, Techniques, Procedures — behavioral fingerprint of an adversary group, more durable than IOCs which change frequently | | Aliases | Threat actors receive different names from different vendors (APT29 = Cozy Bear = The Dukes = Midnight Blizzard = YTTRIUM) | | Attribution | Process of associating an attack with a specific threat actor; requires multiple independent corroborating data points and carries inherent uncertainty | | Cluster | A group of related intrusion activity that may or may not be attributable to a single actor; used when attribution is uncertain | | Intrusion Set | STIX SDO type representing a grouped set of adversarial behaviors with common objectives, even if actor identity is unknown |
development
拋棄式 HTML mockup 比稿:產出 2 到 3 個設計立場不同的變體(密度 / 版式 / 強調軸,不是換色),各附取捨說明,最後給有立場的對比結論。適用:「畫個草圖」「比較 A 版 B 版」「先看方向再做」「給我看幾種做法」。要 production 元件或設計已定案時不適用。
tools
需求不明時的意圖萃取訪談:一次一題、每題附上自己的猜測、聽出「真正想要 vs 覺得應該要」,直到能預測使用者反應(約 95% 信心)才動工。適用:需求缺少對象 / 動機 / 成功標準 / 約束,或使用者點名「訪談我」「先確認一下」「我們確定嗎」。明確自足的指示、純資訊查詢、機械性操作不適用。
development
對非平凡決策啟動新鮮 context 對抗審查(找碴不背書),在修正還便宜的時候抓出錯誤方向。適用:高風險改動(production、資安敏感邏輯、不可逆操作)、不熟的程式碼、要宣稱「這樣是安全的 / 可行的」之前。機械性操作與一行修改不適用。
testing
Reference for writing and editing agent skills well — the vocabulary and principles that make a skill predictable. Consult when authoring, reviewing, or pruning a SKILL.md.