tracking-threat-actor-infrastructure
Threat actor infrastructure tracking involves monitoring and mapping adversary-controlled assets including command-and-control (C2) servers, phishing domains, exploit kit hosts, bulletproof hosting, a
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Installation Guide
How to use tracking-threat-actor-infrastructure on Cursor
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Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
tracking-threat-actor-infrastructure
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches tracking-threat-actor-infrastructure from mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate tracking-threat-actor-infrastructure. Access via /tracking-threat-actor-infrastructure in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
| name | tracking-threat-actor-infrastructure |
| description | Threat actor infrastructure tracking involves monitoring and mapping adversary-controlled assets including command-and-control (C2) servers, phishing domains, exploit kit hosts, bulletproof hosting, a |
| 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 |
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,stix2libraries - 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
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Use Cases
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Steps
- 1Install skill using provided installation command
- 2Test with simple use case relevant to your work
- 3Evaluate output quality and relevance
- 4Iterate on prompts to improve results
- 5Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
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Reviews
- AAanya Chen★★★★★Dec 28, 2024
I recommend tracking-threat-actor-infrastructure for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- CChaitanya Patil★★★★★Dec 24, 2024
Useful defaults in tracking-threat-actor-infrastructure — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- AAanya Garcia★★★★★Dec 24, 2024
Keeps context tight: tracking-threat-actor-infrastructure is the kind of skill you can hand to a new teammate without a long onboarding doc.
- CCamila Agarwal★★★★★Dec 12, 2024
tracking-threat-actor-infrastructure is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- CCarlos Harris★★★★★Nov 27, 2024
tracking-threat-actor-infrastructure has been reliable in day-to-day use. Documentation quality is above average for community skills.
- HHenry Shah★★★★★Nov 19, 2024
Keeps context tight: tracking-threat-actor-infrastructure is the kind of skill you can hand to a new teammate without a long onboarding doc.
- PPiyush G★★★★★Nov 15, 2024
tracking-threat-actor-infrastructure is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- VValentina Diallo★★★★★Nov 15, 2024
I recommend tracking-threat-actor-infrastructure for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- MMin Singh★★★★★Nov 3, 2024
Useful defaults in tracking-threat-actor-infrastructure — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- IIshan Robinson★★★★★Oct 22, 2024
I recommend tracking-threat-actor-infrastructure for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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