external/anthropic-cybersecurity-skills/skills/performing-ip-reputation-analysis-with-shodan/SKILL.md
Analyze IP address reputation using the Shodan API to identify open ports, running services, known vulnerabilities, and hosting context for threat intelligence enrichment and incident triage.
npx skillsauth add seikaikyo/dash-skills performing-ip-reputation-analysis-with-shodanInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Shodan is the world's first search engine for internet-connected devices, continuously scanning the IPv4 and IPv6 address space to catalog open ports, running services, SSL certificates, and known vulnerabilities. This skill covers using the Shodan API and InternetDB free API to enrich IP addresses from security alerts, assess threat levels based on exposed services and vulnerabilities, identify hosting infrastructure patterns, and integrate IP reputation data into SOC triage and threat intelligence workflows.
shodan library (pip install shodan)Each IP record in Shodan contains: open ports and protocols, banner data (service responses), SSL/TLS certificate details, known CVE vulnerabilities, hostname(s) and reverse DNS, ASN and ISP information, geographic location, operating system fingerprint, and historical scan data showing changes over time.
Shodan's free InternetDB API (internetdb.shodan.io) provides quick IP lookups without authentication, returning open ports, hostnames, tags, CPEs, and known vulnerabilities. This is useful for high-volume enrichment where the full Shodan API would hit rate limits.
IP reputation is assessed by combining: number and type of open ports (unusual ports indicate compromise), vulnerable services (unpatched software with known CVEs), hosting type (residential, cloud, VPN/proxy, bulletproof hosting), historical activity (past associations with malware, scanning, spam), and geographic context (countries known for specific threat activity).
import shodan
import json
from datetime import datetime
class ShodanEnricher:
def __init__(self, api_key):
self.api = shodan.Shodan(api_key)
self.info = self.api.info()
print(f"[+] Shodan API initialized. Credits: {self.info.get('scan_credits', 0)}")
def enrich_ip(self, ip_address):
"""Full enrichment of an IP address via Shodan."""
try:
host = self.api.host(ip_address)
enrichment = {
"ip": ip_address,
"organization": host.get("org", ""),
"asn": host.get("asn", ""),
"isp": host.get("isp", ""),
"country": host.get("country_name", ""),
"country_code": host.get("country_code", ""),
"city": host.get("city", ""),
"latitude": host.get("latitude"),
"longitude": host.get("longitude"),
"os": host.get("os", ""),
"ports": host.get("ports", []),
"hostnames": host.get("hostnames", []),
"domains": host.get("domains", []),
"vulns": host.get("vulns", []),
"tags": host.get("tags", []),
"last_update": host.get("last_update", ""),
"services": [],
}
for service in host.get("data", []):
svc = {
"port": service.get("port", 0),
"transport": service.get("transport", "tcp"),
"product": service.get("product", ""),
"version": service.get("version", ""),
"module": service.get("_shodan", {}).get("module", ""),
"banner": service.get("data", "")[:200],
}
if "ssl" in service:
svc["ssl_subject"] = service["ssl"].get("cert", {}).get("subject", {})
svc["ssl_issuer"] = service["ssl"].get("cert", {}).get("issuer", {})
svc["ssl_expires"] = service["ssl"].get("cert", {}).get("expires", "")
enrichment["services"].append(svc)
# Calculate reputation score
enrichment["reputation"] = self._calculate_reputation(enrichment)
print(f"[+] {ip_address}: {len(enrichment['ports'])} ports, "
f"{len(enrichment['vulns'])} vulns, "
f"reputation: {enrichment['reputation']['level']}")
return enrichment
except shodan.APIError as e:
print(f"[-] Shodan error for {ip_address}: {e}")
return None
def _calculate_reputation(self, data):
"""Calculate IP reputation score based on Shodan data."""
score = 0
factors = []
# Vulnerability assessment
vuln_count = len(data.get("vulns", []))
if vuln_count > 10:
score += 40
factors.append(f"{vuln_count} known vulnerabilities")
elif vuln_count > 5:
score += 25
factors.append(f"{vuln_count} known vulnerabilities")
elif vuln_count > 0:
score += 10
factors.append(f"{vuln_count} known vulnerabilities")
# Suspicious port analysis
suspicious_ports = {4444, 5555, 6666, 8888, 9090, 1234, 31337,
6667, 6697, 8080, 8443, 3128, 1080}
open_ports = set(data.get("ports", []))
sus_found = open_ports.intersection(suspicious_ports)
if sus_found:
score += 15
factors.append(f"suspicious ports: {sus_found}")
# Tag-based assessment
malicious_tags = {"self-signed", "cloud", "vpn", "proxy", "tor"}
tags = set(data.get("tags", []))
mal_tags = tags.intersection(malicious_tags)
if mal_tags:
score += 10
factors.append(f"tags: {mal_tags}")
# Too many open ports
port_count = len(data.get("ports", []))
if port_count > 20:
score += 15
factors.append(f"excessive open ports ({port_count})")
level = (
"critical" if score >= 50
else "high" if score >= 35
else "medium" if score >= 15
else "low"
)
return {"score": score, "level": level, "factors": factors}
def enrich_ip_free(self, ip_address):
"""Quick IP enrichment using free InternetDB API."""
import requests
resp = requests.get(f"https://internetdb.shodan.io/{ip_address}", timeout=10)
if resp.status_code == 200:
data = resp.json()
print(f"[+] InternetDB: {ip_address} -> "
f"{len(data.get('ports', []))} ports, "
f"{len(data.get('vulns', []))} vulns")
return data
return None
enricher = ShodanEnricher("YOUR_SHODAN_API_KEY")
result = enricher.enrich_ip("8.8.8.8")
print(json.dumps(result, indent=2, default=str))
import time
def batch_ip_reputation(enricher, ip_list, output_file="ip_reputation.json"):
"""Check reputation for a list of IP addresses."""
results = []
for i, ip in enumerate(ip_list):
result = enricher.enrich_ip(ip)
if result:
results.append(result)
if (i + 1) % 10 == 0:
print(f" [{i+1}/{len(ip_list)}] Processed")
time.sleep(1) # Rate limiting
# Sort by reputation score (highest risk first)
results.sort(key=lambda x: x.get("reputation", {}).get("score", 0), reverse=True)
with open(output_file, "w") as f:
json.dump(results, f, indent=2, default=str)
# Summary
levels = {"critical": 0, "high": 0, "medium": 0, "low": 0}
for r in results:
level = r.get("reputation", {}).get("level", "low")
levels[level] += 1
print(f"\n=== Batch Reputation Summary ===")
print(f"Total IPs: {len(results)}")
for level, count in levels.items():
print(f" {level.upper()}: {count}")
return results
suspicious_ips = ["203.0.113.1", "198.51.100.5", "192.0.2.100"]
results = batch_ip_reputation(enricher, suspicious_ips)
def correlate_infrastructure(enricher, ip_address):
"""Find related infrastructure based on shared attributes."""
host_data = enricher.enrich_ip(ip_address)
if not host_data:
return {}
correlations = {
"same_org": [],
"same_asn": [],
"shared_ssl": [],
}
# Search for same organization
org = host_data.get("organization", "")
if org:
try:
results = enricher.api.search(f'org:"{org}"', limit=20)
for match in results.get("matches", []):
correlations["same_org"].append({
"ip": match.get("ip_str", ""),
"port": match.get("port", 0),
"product": match.get("product", ""),
})
except shodan.APIError:
pass
# Search for same SSL certificate
for service in host_data.get("services", []):
ssl_subject = service.get("ssl_subject", {})
if ssl_subject:
cn = ssl_subject.get("CN", "")
if cn:
try:
results = enricher.api.search(f'ssl.cert.subject.CN:"{cn}"', limit=20)
for match in results.get("matches", []):
correlations["shared_ssl"].append({
"ip": match.get("ip_str", ""),
"cn": cn,
})
except shodan.APIError:
pass
print(f"[+] Infrastructure correlations for {ip_address}:")
print(f" Same org: {len(correlations['same_org'])} hosts")
print(f" Shared SSL: {len(correlations['shared_ssl'])} hosts")
return correlations
development
拋棄式 HTML mockup 比稿:產出 2 到 3 個設計立場不同的變體(密度 / 版式 / 強調軸,不是換色),各附取捨說明,最後給有立場的對比結論。適用:「畫個草圖」「比較 A 版 B 版」「先看方向再做」「給我看幾種做法」。要 production 元件或設計已定案時不適用。
tools
需求不明時的意圖萃取訪談:一次一題、每題附上自己的猜測、聽出「真正想要 vs 覺得應該要」,直到能預測使用者反應(約 95% 信心)才動工。適用:需求缺少對象 / 動機 / 成功標準 / 約束,或使用者點名「訪談我」「先確認一下」「我們確定嗎」。明確自足的指示、純資訊查詢、機械性操作不適用。
development
對非平凡決策啟動新鮮 context 對抗審查(找碴不背書),在修正還便宜的時候抓出錯誤方向。適用:高風險改動(production、資安敏感邏輯、不可逆操作)、不熟的程式碼、要宣稱「這樣是安全的 / 可行的」之前。機械性操作與一行修改不適用。
testing
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