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分析 TLS 憑證透明度日誌

透過 crt.sh 及 pycrtsh 查詢憑證透明度日誌,以偵測釣魚基礎設施與品牌冒充。

分析 TLS 憑證透明度日誌 是什麼?

此技能旨在協助安全分析師與開發者,利用憑證透明度 (CT) 日誌中公開的 TLS 憑證資訊,主動識別釣魚基礎設施與品牌冒充攻擊。它透過 crt.sh 服務與 pycrtsh 函式庫,自動化查詢與公司網域相似的憑證,並運用編輯距離 (Levenshtein distance) 等技術偵測錯字域名變體。技能支援 Python 環境,提供可直接執行的程式碼範例,並包含完整的分析步驟:從查詢比對、異常 CA 標記到與已知威脅情報交叉比對。此工具特別適合 SOC 分析師用於事件調查、威脅狩獵或驗證安全監控覆蓋率,並強調需在獲得授權的測試環境中執行。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-tls-certificate-transparency-logs

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說明文件

分析 TLS 憑證透明度日誌 是做什麼的?

使用時機

  • 調查需要分析 TLS 憑證透明度日誌的安全事件時
  • 建立此領域的檢測規則或威脅狩獵查詢時
  • SOC 分析師需要此分析類型的結構化程序時
  • 驗證相關攻擊技巧的安全監控覆蓋率時

先決條件

  • 熟悉安全營運概念與工具
  • 能夠存取測試或實驗環境以安全執行
  • Python 3.8+ 與必要依賴套件已安裝
  • 針對任何測試活動取得適當授權

操作說明

查詢 crt.sh 憑證透明度資料庫,找出為與您組織品牌相似網域所發行的憑證,以偵測釣魚基礎設施。

from pycrtsh import Crtsh

c = Crtsh()
# 搜尋符合某個網域的憑證
certs = c.search("example.com")
for cert in certs:
    print(cert["id"], cert["name_value"])

# 取得完整的憑證詳細資訊
details = c.get(certs[0]["id"], type="id")

關鍵分析步驟:

  1. 查詢 crt.sh 找出所有符合您網域模式的憑證
  2. 識別含有錯字域名變體(編輯距離)的憑證
  3. 標記來自非預期 CA 的憑證
  4. 監控可疑子網域上的萬用字元憑證
  5. 與已知的釣魚基礎設施交叉比對

範例

from pycrtsh import Crtsh
c = Crtsh()
certs = c.search("%.example.com")
for cert in certs:
    print(f"發行者: {cert.get('issuer_name')}, 網域: {cert.get('name_value')}")

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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