performing-ip-reputation-analysis-with-shodan使用 Shodan API 分析 IP 地址声誉，识别开放端口、运行服务、已知漏洞和托管上下文，用于威胁情报富化和事件分类。
Independent GitHub snapshot · Automated classification · Original documentation governs
Shodan 是全球首个互联网设备搜索引擎，持续扫描 IPv4 和 IPv6 地址空间，记录开放端口、运行服务、SSL 证书和已知漏洞。本技能涵盖使用 Shodan API 和 InternetDB 免费 API 富化来自安全告警的 IP 地址、根据暴露服务和漏洞评估威胁级别、识别托管基础设施模式，以及将 IP 声誉数据集成到 SOC 分类和威胁情报工作流中。
shodan 库（pip install shodan）Shodan 中的每条 IP 记录包含：开放端口和协议、Banner 数据（服务响应）、SSL/TLS 证书详情、已知 CVE 漏洞、主机名和反向 DNS、ASN 和 ISP 信息、地理位置、操作系统指纹，以及显示变化历史的历史扫描数据。
Shodan 的免费 InternetDB API（internetdb.shodan.io）无需身份验证即可快速查询 IP，返回开放端口、主机名、标签、CPE 和已知漏洞。适用于全量 Shodan API 可能触及速率限制的高容量富化场景。
通过以下维度综合评估 IP 声誉：开放端口数量和类型（异常端口表明可能遭到攻陷）、易受攻击服务（含已知 CVE 的未修补软件）、托管类型（住宅、云端、VPN/代理、防弹托管）、历史活动（过去与恶意软件、扫描、垃圾邮件的关联），以及地理背景（以特定威胁活动著称的国家/地区）。
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 已初始化。剩余扫描积分：{self.info.get('scan_credits', 0)}")
def enrich_ip(self, ip_address):
"""通过 Shodan 对 IP 地址进行完整富化。"""
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)
# 计算声誉评分
enrichment["reputation"] = self._calculate_reputation(enrichment)
print(f"[+] {ip_address}：{len(enrichment['ports'])} 个端口，"
f"{len(enrichment['vulns'])} 个漏洞，"
f"声誉等级：{enrichment['reputation']['level']}")
return enrichment
except shodan.APIError as e:
print(f"[-] {ip_address} 的 Shodan 查询出错：{e}")
return None
def _calculate_reputation(self, data):
"""根据 Shodan 数据计算 IP 声誉评分。"""
score = 0
factors = []
# 漏洞评估
vuln_count = len(data.get("vulns", []))
if vuln_count > 10:
score += 40
factors.append(f"{vuln_count} 个已知漏洞")
elif vuln_count > 5:
score += 25
factors.append(f"{vuln_count} 个已知漏洞")
elif vuln_count > 0:
score += 10
factors.append(f"{vuln_count} 个已知漏洞")
# 可疑端口分析
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"可疑端口：{sus_found}")
# 基于标签的评估
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"标签：{mal_tags}")
# 开放端口过多
port_count = len(data.get("ports", []))
if port_count > 20:
score += 15
factors.append(f"开放端口过多（{port_count} 个）")
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):
"""使用免费 InternetDB API 快速富化 IP。"""
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', []))} 个端口，"
f"{len(data.get('vulns', []))} 个漏洞")
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"):
"""检查 IP 地址列表的声誉。"""
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)}] 已处理")
time.sleep(1) # 速率限制
# 按声誉评分降序排列（最高风险在前）
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)
# 汇总
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=== 批量声誉汇总 ===")
print(f"IP 总数：{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):
"""根据共享属性发现相关基础设施。"""
host_data = enricher.enrich_ip(ip_address)
if not host_data:
return {}
correlations = {
"same_org": [],
"same_asn": [],
"shared_ssl": [],
}
# 搜索同一组织
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
# 搜索相同 SSL 证书
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"[+] {ip_address} 的基础设施关联：")
print(f" 同一组织：{len(correlations['same_org'])} 台主机")
print(f" 共享 SSL：{len(correlations['shared_ssl'])} 台主机")
return correlations