Agent skill

Tracking Threat Actor Infrastructure

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Discovers and maps adversary-controlled infrastructure (C2 servers, phishing domains, exploit-kit hosts, bulletproof hosting) by pivoting across passive DNS, certificate transparency logs…

Apache-2.0Auto-check passedSecurity

Install Tracking Threat Actor Infrastructure

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill tracking-threat-actor-infrastructure -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills tracking-threat-actor-infrastructure --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/tracking-threat-actor-infrastructure .claude/skills/tracking-threat-actor-infrastructure && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
tracking-threat-actor-infrastructure
GitHub stars
34k
Token cost
~2.9k tokens
SKILL.md length
379 words
Files
8 (incl. scripts, references, assets)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Discovers and maps adversary-controlled infrastructure (C2 servers, phishing domains, exploit-kit hosts, bulletproof hosting) by pivoting across passive DNS, certificate transparency logs…

  • Works in 4 steps: Shodan Infrastructure Discovery → Passive DNS Pivoting → Certificate Transparency Monitoring → …
  • Tracking threat actor infrastructure
  • SKILL.md covers Overview, When to Use, Prerequisites and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder; reaches crt.sh and api.passivetotal.org

What it does

Tracking Threat Actor Infrastructure is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. 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.

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts, reference files and assets (for example `assets/template.md`, `references/api-reference.md` and `references/standards.md`).

It sits in Security, covering OSINT. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.

When your agent uses it

  • Tracking threat actor infrastructure
  • Expanding a known IOC into related assets
  • Producing STIX-based threat intelligence during a CTI investigation

Example prompts

  • “Use the tracking-threat-actor-infrastructure skill to discover and maps adversary-controlled infrastructure (C2 servers, phishing domains…”
  • “/tracking-threat-actor-infrastructure”

Requirements

  • Python 3
  • A credential in YOUR_SHODAN_API_KEY

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Shodan Infrastructure Discovery
  2. Passive DNS Pivoting
  3. Certificate Transparency Monitoring
  4. Infrastructure Correlation and Timeline

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • crt.sh
    • api.passivetotal.org
    • api.securitytrails.com

    Also links to:

    • developer.shodan.io
    • search.censys.io
    • securitytrails.com
    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Tracking Threat Actor Infrastructure loads about 2.9k tokens when it runs, and up to ~4.4k if it reads all its reference files. Until then it costs about 115 tokens; SKILL.md has 379 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~115
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 379 words, ~2,882 tokens.

Download SKILL.mdSave it as .claude/skills/tracking-threat-actor-infrastructure/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
tracking-threat-actor-infrastructure
description
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.
domain
cybersecurity
subdomain
threat-intelligence
tags
threat-intelligence, cti, ioc, mitre-attack, stix, infrastructure-tracking, shodan, censys, passive-dns
version
1.0
author
mahipal
license
Apache-2.0
nist_csf
ID.RA-01, ID.RA-05, DE.CM-01, DE.AE-02
mitre_attack
T1591, T1592, T1593, T1589, T1566
mitre_f3.version
1.1
mitre_f3.tactics
reconnaissance, resource-development

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.

Show full SKILL.md (153 more words)Show less
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
python
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
python
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
python
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
python
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

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (scripts, references, assets) in skills/tracking-threat-actor-infrastructure of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • assets/template.md
  • references/api-reference.md
  • references/standards.md
  • references/workflows.md
  • scripts/agent.py
  • scripts/process.py

Open the folder on GitHubat commit 54a7988

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ShadowBroker Intelligence ClientBigBodyCobain/Shadowbroker11k—~8.9kAutomated safety check: WarnAGPL-3.0
Awesome Osint Operatorshoyann/RZK-The-Hunter141—~4.8kAutomated safety check: PassCC-BY-SA-4.0
Run Claude Osintelementalsouls/Claude-OSINT2.8k—~1.2kAutomated safety check: PassMIT

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Categories

Questions about Tracking Threat Actor Infrastructure

What does Tracking Threat Actor Infrastructure do?

Discovers and maps adversary-controlled infrastructure (C2 servers, phishing domains, exploit-kit hosts, bulletproof hosting) by pivoting across passive DNS, certificate transparency logs…. Tracking Threat Actor Infrastructure is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. 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).

When should I use Tracking Threat Actor Infrastructure?

Tracking Threat Actor Infrastructure fits situations like: tracking threat actor infrastructure; expanding a known IOC into related assets; producing STIX-based threat intelligence during a CTI investigation.

How do I install Tracking Threat Actor Infrastructure in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill tracking-threat-actor-infrastructure -a claude-code`. Or copy the skill folder (skills/tracking-threat-actor-infrastructure in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/tracking-threat-actor-infrastructure in your project. Claude Code loads it when a task matches its description.

How do I install Tracking Threat Actor Infrastructure in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill tracking-threat-actor-infrastructure -a codex`. Or copy the skill folder (skills/tracking-threat-actor-infrastructure in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/tracking-threat-actor-infrastructure in your project. Codex loads it when a task matches its description.

Can I use Tracking Threat Actor Infrastructure in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill tracking-threat-actor-infrastructure -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tracking-threat-actor-infrastructure, .gemini/skills/tracking-threat-actor-infrastructure, .github/skills/tracking-threat-actor-infrastructure and .opencode/skills/tracking-threat-actor-infrastructure in your project.

What does Tracking Threat Actor Infrastructure need to run?

Going by SKILL.md and its folder, Tracking Threat Actor Infrastructure needs Python for the scripts in its folder. Our summary lists: Python 3; A credential in YOUR_SHODAN_API_KEY.

Does Tracking Threat Actor Infrastructure access the network?

SKILL.md names 7 domains. In commands or code: crt.sh, api.passivetotal.org and api.securitytrails.com; the agent is likely to contact these when it follows the instructions. As links in the text: developer.shodan.io, search.censys.io, securitytrails.com and github.com. This is read from the text; nothing was executed.

Is Tracking Threat Actor Infrastructure safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Tracking Threat Actor Infrastructure use?

Tracking Threat Actor Infrastructure is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tracking Threat Actor Infrastructure use?

About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.5k tokens, read only when the agent opens those files.

What are the alternatives to Tracking Threat Actor Infrastructure?

Skills that share tags, products or a category with Tracking Threat Actor Infrastructure: Metabigor OSINT Recon (j3ssie/metabigor, 1.9k stars), Ctf Osint (ljagiello/ctf-skills, 3.4k stars), ShadowBroker Intelligence Client (BigBodyCobain/Shadowbroker, 11k stars) and Awesome Osint Operator (shoyann/RZK-The-Hunter, 141 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tracking Threat Actor Infrastructure?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.