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mukul975/anthropic-cybersecurity-skills95 installs

tracking-threat-actor-infrastructure

Discovers and maps adversary-controlled infrastructure (C2 servers, phishing domains, exploit-kit hosts, bulletproof hosting) by pivoting across passive DNS, certificate transparency logs, Shodan/Censys scans, WHOIS records, and network fingerprints (JARM/JA3S). Use when tracking threat actor infrastructure, expanding a known IOC into related assets, or producing STIX-based threat intelligence during a CTI investigation.

How do I install this agent skill?

npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill tracking-threat-actor-infrastructure
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    This skill tracks threat actor infrastructure by querying external security platforms and fingerprinting network targets. While it handles untrusted metadata from the internet, this behavior is central to its purpose as a threat intelligence tool, and no malicious patterns were detected.

  • Socketpass

    No alerts

  • Snykwarn

    Risk: MEDIUM · 1 issue

  • Runlayerwarn

    6/8 files flagged

What does this agent skill do?

Tracking Threat Actor Infrastructure

Overview

Threat actor infrastructure tracking involves monitoring and mapping adversary-controlled assets including command-and-control (C2) servers, phishing domains, exploit kit hosts, bulletproof hosting, and staging servers. This skill covers using passive DNS, certificate transparency logs, Shodan/Censys scanning, WHOIS analysis, and network fingerprinting to discover, track, and pivot across threat actor infrastructure over time.

When to Use

  • When managing security operations that require tracking threat actor infrastructure
  • When improving security program maturity and operational processes
  • When establishing standardized procedures for security team workflows
  • When integrating threat intelligence or vulnerability data into operations

Prerequisites

  • Python 3.9+ with shodan, censys, requests, stix2 libraries
  • API keys: Shodan, Censys, VirusTotal, SecurityTrails, PassiveTotal
  • Understanding of DNS, TLS/SSL certificates, IP allocation, ASN structure
  • Familiarity with passive DNS and certificate transparency concepts
  • Access to domain registration (WHOIS) lookup services

Key Concepts

Infrastructure Pivoting

Pivoting is the technique of using one known indicator to discover related infrastructure. Starting from a known C2 IP address, analysts can pivot via: passive DNS (find domains), reverse WHOIS (find related registrations), SSL certificates (find shared certs), SSH key fingerprints, HTTP response fingerprints, JARM/JA3S hashes, and WHOIS registrant data.

Passive DNS

Passive DNS databases record DNS query/response data observed at recursive resolvers. This allows analysts to find historical domain-to-IP mappings, discover domains hosted on a known C2 IP, and identify fast-flux or domain generation algorithm (DGA) behavior.

Certificate Transparency

Certificate Transparency (CT) logs publicly record all SSL/TLS certificates issued by CAs. Monitoring CT logs reveals new certificates registered for suspicious domains, helping identify phishing sites and C2 infrastructure before they become active.

Network Fingerprinting

  • JARM: Active TLS server fingerprint (hash of TLS handshake responses)
  • JA3S: Passive TLS server fingerprint (hash of Server Hello)
  • HTTP Headers: Server banners, custom headers, response patterns
  • Favicon Hash: Hash of HTTP favicon for server identification

Workflow

Step 1: Shodan Infrastructure Discovery

import shodan

api = shodan.Shodan("YOUR_SHODAN_API_KEY")

def discover_infrastructure(ip_address):
    """Discover services and metadata for a target IP."""
    try:
        host = api.host(ip_address)
        return {
            "ip": host["ip_str"],
            "org": host.get("org", ""),
            "asn": host.get("asn", ""),
            "isp": host.get("isp", ""),
            "country": host.get("country_name", ""),
            "city": host.get("city", ""),
            "os": host.get("os"),
            "ports": host.get("ports", []),
            "vulns": host.get("vulns", []),
            "hostnames": host.get("hostnames", []),
            "domains": host.get("domains", []),
            "tags": host.get("tags", []),
            "services": [
                {
                    "port": svc.get("port"),
                    "transport": svc.get("transport"),
                    "product": svc.get("product", ""),
                    "version": svc.get("version", ""),
                    "ssl_cert": svc.get("ssl", {}).get("cert", {}).get("subject", {}),
                    "jarm": svc.get("ssl", {}).get("jarm", ""),
                }
                for svc in host.get("data", [])
            ],
        }
    except shodan.APIError as e:
        print(f"[-] Shodan error: {e}")
        return None

def search_c2_framework(framework_name):
    """Search Shodan for known C2 framework signatures."""
    c2_queries = {
        "cobalt-strike": 'product:"Cobalt Strike Beacon"',
        "metasploit": 'product:"Metasploit"',
        "covenant": 'http.html:"Covenant" http.title:"Covenant"',
        "sliver": 'ssl.cert.subject.cn:"multiplayer" ssl.cert.issuer.cn:"operators"',
        "havoc": 'http.html_hash:-1472705893',
    }

    query = c2_queries.get(framework_name.lower(), framework_name)
    results = api.search(query, limit=100)

    hosts = []
    for match in results.get("matches", []):
        hosts.append({
            "ip": match["ip_str"],
            "port": match["port"],
            "org": match.get("org", ""),
            "country": match.get("location", {}).get("country_name", ""),
            "asn": match.get("asn", ""),
            "timestamp": match.get("timestamp", ""),
        })

    return hosts

Step 2: Passive DNS Pivoting

import requests

def passive_dns_lookup(indicator, api_key, indicator_type="ip"):
    """Query SecurityTrails for passive DNS records."""
    base_url = "https://api.securitytrails.com/v1"
    headers = {"APIKEY": api_key, "Accept": "application/json"}

    if indicator_type == "ip":
        url = f"{base_url}/search/list"
        payload = {
            "filter": {"ipv4": indicator}
        }
        resp = requests.post(url, json=payload, headers=headers, timeout=30)
    else:
        url = f"{base_url}/domain/{indicator}/subdomains"
        resp = requests.get(url, headers=headers, timeout=30)

    if resp.status_code == 200:
        return resp.json()
    return None


def query_passive_total(indicator, user, api_key):
    """Query PassiveTotal for passive DNS and WHOIS data."""
    base_url = "https://api.passivetotal.org/v2"
    auth = (user, api_key)

    # Passive DNS
    pdns_resp = requests.get(
        f"{base_url}/dns/passive",
        params={"query": indicator},
        auth=auth,
        timeout=30,
    )

    # WHOIS
    whois_resp = requests.get(
        f"{base_url}/whois",
        params={"query": indicator},
        auth=auth,
        timeout=30,
    )

    results = {}
    if pdns_resp.status_code == 200:
        results["passive_dns"] = pdns_resp.json().get("results", [])
    if whois_resp.status_code == 200:
        results["whois"] = whois_resp.json()

    return results

Step 3: Certificate Transparency Monitoring

import requests

def search_ct_logs(domain):
    """Search Certificate Transparency logs via crt.sh."""
    resp = requests.get(
        f"https://crt.sh/?q=%.{domain}&output=json",
        timeout=30,
    )

    if resp.status_code == 200:
        certs = resp.json()
        unique_domains = set()
        cert_info = []

        for cert in certs:
            name_value = cert.get("name_value", "")
            for name in name_value.split("\n"):
                unique_domains.add(name.strip())

            cert_info.append({
                "id": cert.get("id"),
                "issuer": cert.get("issuer_name", ""),
                "common_name": cert.get("common_name", ""),
                "name_value": name_value,
                "not_before": cert.get("not_before", ""),
                "not_after": cert.get("not_after", ""),
                "serial_number": cert.get("serial_number", ""),
            })

        return {
            "domain": domain,
            "total_certificates": len(certs),
            "unique_domains": sorted(unique_domains),
            "certificates": cert_info[:50],
        }
    return None


def monitor_new_certs(domains, interval_hours=1):
    """Monitor for newly issued certificates for a list of domains."""
    from datetime import datetime, timedelta

    cutoff = (datetime.utcnow() - timedelta(hours=interval_hours)).isoformat()
    new_certs = []

    for domain in domains:
        result = search_ct_logs(domain)
        if result:
            for cert in result.get("certificates", []):
                if cert.get("not_before", "") > cutoff:
                    new_certs.append({
                        "domain": domain,
                        "cert": cert,
                    })

    return new_certs

Step 4: Infrastructure Correlation and Timeline

from datetime import datetime

def build_infrastructure_timeline(indicators):
    """Build a timeline of infrastructure changes."""
    timeline = []

    for ind in indicators:
        if "passive_dns" in ind:
            for record in ind["passive_dns"]:
                timeline.append({
                    "timestamp": record.get("firstSeen", ""),
                    "event": "dns_resolution",
                    "source": record.get("resolve", ""),
                    "target": record.get("value", ""),
                    "record_type": record.get("recordType", ""),
                })

        if "certificates" in ind:
            for cert in ind["certificates"]:
                timeline.append({
                    "timestamp": cert.get("not_before", ""),
                    "event": "certificate_issued",
                    "domain": cert.get("common_name", ""),
                    "issuer": cert.get("issuer", ""),
                })

    timeline.sort(key=lambda x: x.get("timestamp", ""))
    return timeline

Validation Criteria

  • Shodan/Censys queries return infrastructure details for target IPs
  • Passive DNS reveals historical domain-IP mappings
  • Certificate transparency search finds associated domains
  • Infrastructure pivoting discovers new related indicators
  • Timeline shows infrastructure evolution over time
  • Results are exportable as STIX 2.1 Infrastructure objects

References

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/mukul975/anthropic-cybersecurity-skills/tracking-threat-actor-infrastructure">View tracking-threat-actor-infrastructure on skillZs</a>