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使用 MITRE Navigator 分析威脅行為者 TTP

利用 attackcti Python 函式庫查詢 STIX/TAXII 資料,將進階持續性威脅(APT)群體的 TTP 對應至 MITRE ATT&CK 框架,並產生 ATT&CK Navigator 圖層檔案,用以視覺化及比較防禦覆蓋率與攻擊者輪廓。適用於分析 APT 群體。

使用 MITRE Navigator 分析威脅行為者 TTP 是什麼?

此技能可協助分析師將特定的 APT 群體戰術、技術與程序(TTP)系統性地對應至 MITRE ATT&CK 框架。透過 attackcti 函式庫自動查詢 STIX/TAXII 資料來源,提取與目標威脅群體相關的技術,並以 ATT&CK Navigator 圖層 JSON 格式輸出結果。此圖層檔案可直接匯入 Navigator 進行視覺化比較,或疊加現有檢測覆蓋率,以識別防禦缺口。技能支援 Python 3.8 以上環境,需預先安裝 attackcti 與 stix2 函式庫,並建議搭配 MITRE ATT&CK Navigator 網頁介面或本地實例使用。產出的圖層包含技術 ID、評分與註解,便於團隊進行防禦規劃與威脅狩獵。

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說明文件

使用 MITRE Navigator 分析威脅行為者 TTP 是做什麼的?

概述

MITRE ATT&CK Navigator 是一個用於註記與視覺化 ATT&CK 矩陣的網頁應用程式。搭配 attackcti Python 函式庫(透過 TAXII 查詢 ATT&CK STIX 資料),分析師可以程式化地產生對應特定威脅群體 TTP 的 Navigator 圖層檔案、比較多個群體,並評估針對已知敵人的檢測覆蓋缺口。

使用時機

  • 當調查安全事件,需要分析威脅行為者 TTP 時
  • 當為此領域建立檢測規則或威脅狩獵查詢時
  • 當 SOC 分析師需要此分析類型的結構化程序時
  • 當驗證相關攻擊技術的安全監控覆蓋率時

先決條件

  • Python 3.8+,並安裝 attackcti 與 stix2 函式庫
  • MITRE ATT&CK Navigator(網頁 UI 或本地實例)
  • 了解 STIX 2.1 物件與關係

步驟

  1. 使用 attackcti 查詢目標威脅群體的 ATT&CK STIX 資料
  2. 透過 STIX 關係提取與該群體相關的技術
  3. 產生含有技術註記的 ATT&CK Navigator 圖層 JSON
  4. 疊加檢測覆蓋率以識別缺口
  5. 匯出圖層供團隊審查與防禦規劃

預期輸出

{
  "name": "APT29 TTPs",
  "domain": "enterprise-attack",
  "techniques": [
    {"techniqueID": "T1566.001", "score": 1, "comment": "魚叉式網路釣魚附件"},
    {"techniqueID": "T1059.001", "score": 1, "comment": "PowerShell"}
  ]
}

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

abusing-dpapi-for-credential-access

Extract and decrypt Windows DPAPI-protected secrets (Credential Manager, browser logins/cookies, Wi-Fi credentials, KeePass keys) online or offline using SharpDPAPI, SharpChrome, Mimikatz, or Impacket

abusing-shadow-credentials-for-privesc

Take over Active Directory accounts by writing attacker-controlled public keys to msDS-KeyCredentialLink (Shadow Credentials) with pyWhisker, Whisker, or Certipy, then authenticate via PKINIT to recover the target

achieving-cmmc-level-2-compliance

>-

acquiring-disk-image-with-dd-and-dcfldd

Create forensically sound bit-for-bit disk images with dd or dcfldd on a Linux forensic workstation, preserving evidence integrity through hash verification (MD5/SHA) during acquisition. Use when imaging a suspect drive, USB device, or memory card for investigation, preserving volatile disk evidence during incident response, or producing a verified copy for legal or law-enforcement proceedings before any destructive analysis.

analyzing-active-directory-acl-abuse

Detect dangerous ACL misconfigurations in Active Directory using ldap3

analyzing-android-malware-with-apktool

Perform static analysis of Android APK malware using apktool for resource decompilation, jadx for Java source recovery, and androguard for manifest inspection, dangerous permission-combination detection, and identification of obfuscated code, dynamic code loading, and reflection-based API calls. Use to statically triage a suspicious APK without executing it or to build mobile malware detection rules.

analyzing-api-gateway-access-logs

Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect

analyzing-apt-group-with-mitre-navigator

Query ATT&CK data with attackcti, mitreattack-python, and stix2, then build MITRE ATT&CK Navigator layers and multi-layer heatmap overlays mapping one or more APT groups

analyzing-azure-activity-logs-for-threats

Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query

analyzing-bootkit-and-rootkit-samples

Analyzes bootkit and advanced rootkit malware infecting the Master

analyzing-browser-forensics-with-hindsight

Parse Chromium-based browser databases with Hindsight to extract and correlate browsing history, downloads, cookies, cached content, autofill data, saved passwords, and extensions from Chrome, Edge, Brave, Opera, and Vivaldi into a unified timeline (XLSX, JSON, or SQLite output). Use during incident response, insider-threat investigations, or criminal cases when you need to reconstruct a user

analyzing-campaign-attribution-evidence

Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP consistency, malware code similarity, and timing/language artifacts into confidence-weighted attribution assessments. Use when an incident investigation needs a defensible attribution confidence level.

analyzing-certificate-transparency-for-phishing

Monitor Certificate Transparency logs using crt.sh and Certstream to

analyzing-cloud-storage-access-patterns

Detect abnormal access in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics for after-hours bulk downloads, new-IP access, and API-call spikes (e.g. GetObject) via statistical baselines and time-series anomaly detection. Use when investigating suspected cloud data exfiltration or building related detection rules.

analyzing-cobalt-strike-beacon-configuration

Extract and analyze Cobalt Strike beacon configuration from PE files

analyzing-cobaltstrike-malleable-c2-profiles

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.

analyzing-command-and-control-communication

Analyzes malware C2 communication over HTTP, HTTPS, DNS, and custom

analyzing-cyber-kill-chain

Analyzes intrusion activity against the Lockheed Martin Cyber Kill Chain

analyzing-disk-image-with-autopsy

Perform comprehensive forensic analysis of raw (dd), E01, or AFF disk images with Autopsy and The Sleuth Kit, recovering deleted files, examining metadata and embedded artifacts, keyword searching, and building investigation timelines with visual reports. Use for structured analysis of a forensic disk image or when stakeholders need visual reports from evidence.

analyzing-dns-logs-for-exfiltration

Analyzes DNS query logs to detect data exfiltration via DNS tunneling,

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