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analyzing-certificate-transparency-for-phishing

Monitor Certificate Transparency logs using crt.sh and Certstream to detect phishing domains, lookalike certificates, and unauthorized certificate issuance…

Skill by RobotFlow-Labs

IndexedApache-2.0★ 2
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Monitor Certificate Transparency logs using crt.sh and Certstream to detect phishing domains, lookalike certificates, and unauthorized certificate issuance targeting your organization.

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What's inside

Skill 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.
License
Apache-2.0
Instructions
303 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts
  • Instructions call the network

Files (4)

  • LICENSE
  • SKILL.md
  • api-reference.md · references/
  • agent.py · scripts/

SKILL.md (first lines)

# 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.

## 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.

## Practical Steps

### 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, domain, include_expired=False):
        """Query crt.sh for certificates matching a domain."""
        params = {
            "q": f"%.{domain}",
            "output": "json",
        }
        if not include_expired:
            params["exclude"] = "expired"

        resp = requests.get(self.CRT_SH_URL, params=params, timeout=30)
        if resp.status_code == 200:
            certs = resp.json()
            print(f"[+] crt.sh: {len(certs)} certificates for *.{domain}")
            return certs
        return []

    def find_suspicious_certs(self, domain):
        """Find certificates that may be phishing attempts."""
        certs = self.query_crt_sh(domain)
        suspicious = []

        for cert in certs:
            common_name = cert.get("common_name", "").lower()
            name_value = cert.get("name_value", "").lower()
            issuer = cert.get("issuer_name", "")
            not_before = cert.get("not_before", "")
            not_after = cert.get("not_after", "")

            # Check for exact domain matches (legitimate)
            extracted = tldextract.extract(common_name)
            cert_domain = f"{extracted.domain}.{extracted.suffix}"
            if cert_domain == domain:
                continue  # Legitimate certificate

            # Flag suspicious patterns
            flags = []
            if domain.replace(".", "") in common_name.replace(".", ""):
                flags.append("contains target domain string")
            if any(kw in common_name for kw in self.brand_keywords):
                flags.append("contains brand keyword")
            if "let's encrypt" in issuer.lower():
                flags.append("free CA (Let's Encrypt)")

            if flags:
                suspicious.append({
                    "common_name": cert.get("common_name", ""),
                    "name_value": cert.get("name_value", ""),
                    "issuer": issuer,
                    "not_before": not_before,
                    "not_after": not_after,
                    "serial": cert.get("serial_number", ""),
                    "flags": flags,
                    "crt_sh_id": cert.get("id", ""),
                    "crt_sh_url": f"https://crt.sh/?id={cert.get('id', '')}",
                })

        print(f"[+] Found {len(suspicious)} suspicious certificates")
        return suspicious

monitor = CTLogMonitor(
    monitored_domains=["mycompany.com", "mycompany.org"],
    brand_keywords=["mycompany", "mybrand", "myproduct"],
)
suspicious = monitor.find_suspicious_certs("mycompany.com")
for cert in suspicious[:5]:
    print(f"  [{cert['common_name']}] Flags: {cert['flags']}")
```

### Step 2: Real-Time Monitoring with Certstream

```python
import certstream
import Levenshtein
import re
from datetime import datetime

From RobotFlow-Labs/skills-repo, Apache-2.0.

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Last commit (this folder)
Apr 1, 2026 (7 months ago)

From GitHub (fetched Oct 24, 2026).

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License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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analyzing-certificate-transparency-for-phishing skill. Agent Mart. https://agentmart.dev/skills/robotflow-labs-analyzing-certificate-transparency-for-phishing (last updated 2026-10-24)