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analyzing-certificate-transparency-for-phishing

Relevant threat-intelligence specialty, but narrow.

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来源mukul975/anthropic-cybersecurity-skills外部来源
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SKILL.md

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---
name: analyzing-certificate-transparency-for-phishing
description: Monitor Certificate Transparency logs using crt.sh and Certstream to
  detect phishing domains, lookalike certificates, and unauthorized certificate issuance
  targeting your organization.
domain: cybersecurity
subdomain: threat-intelligence
tags:
- certificate-transparency
- ct-logs
- phishing
- crt-sh
- certstream
- ssl
- domain-monitoring
- threat-intelligence
version: '1.0'
author: mahipal
license: Apache-2.0
atlas_techniques:
- AML.T0052
nist_csf:
- ID.RA-01
- ID.RA-05
- DE.CM-01
- DE.AE-02
mitre_attack:
- T1583.001
- T1583.004
- T1566.002
- T1608.005
- T1596.003
mitre_f3:
  version: '1.1'
  tactics:
  - resource-development
  - reconnaissance
  - initial-access
  techniques:
  - id: T1583.001
    name: 'Acquire Infrastructure: Domains'
    tactic: resource-development
    source: attack
  - id: F1020.002
    name: 'Create Fake Materials: Fake Website'
    tactic: resource-development
    source: f3
  - id: T1593
    name: Search Open Websites/Domains
    tactic: reconnaissance
    source: attack
  - id: T1598
    name: Phishing for Information
    tactic: reconnaissance
    source: attack
  - id: T1660
    name: Phishing
    tactic: initial-access
    source: attack
---
# Analyzing Certificate Transparency for Phishing

## Overview

Certificate Transparency (CT) is an Internet security standard that creates a public, append-only log of all issued SSL/TLS certificates. Monitoring CT logs enables early detection of phishing domains that register certificates mimicking legitimate brands, unauthorized certificate issuance for owned domains, and certificate-based attack infrastructure. This skill covers querying CT logs via crt.sh, real-time monitoring with Certstream, building automated alerting for suspicious certificates, and integrating findings into threat intelligence workflows.


## When to Use

- When investigating security incidents that require analyzing certificate transparency for phishing
- 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 `requests`, `certstream`, `tldextract`, `Levenshtein` libraries
- Access to crt.sh (https://crt.sh/) for historical CT log queries
- Certstream (https://certstream.calidog.io/) for real-time monitoring
- List of organization domains and brand keywords to monitor
- Understanding of SSL/TLS certificate structure and issuance process

## Key Concepts

### Certificate Transparency Logs

CT logs are cryptographically assured, publicly auditable, append-only records of TLS certificate issuance. Major CAs (Let's Encrypt, DigiCert, Sectigo, Google Trust Services) submit all issued certificates to multiple CT logs. As of 2025, Chrome and Safari require CT for all publicly trusted certificates.

### Phishing Detection via CT

Attackers register lookalike domains and obtain free certificates (often from Let's Encrypt) to make phishing sites appear legitimate with HTTPS. CT monitoring detects these early because the certificate appears in logs before the phishing campaign launches, providing a window for proactive blocking.

### crt.sh Database

crt.sh is a free web interface and PostgreSQL database operated by Sectigo that indexes CT logs. It supports wildcard searches (`%.example.com`), direct SQL queries, and JSON API responses. It tracks certificate issuance, expiration, and revocation across all major CT logs.

## Workflow

### Step 1: Query crt.sh for Certificate History

```python
import requests
import json
from datetime import datetime
import tldextract

class CTLogMonitor:
    CRT_SH_URL = "https://crt.sh"

    def __init__(self, monitored_domains, brand_keywords):
        self.monitored_domains = monitored_domains
        self.brand_keywords = [k.lower() for k in brand_keywords]

    def query_crt_sh(self,
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