
ABUSE.MOM — 规矩点,否则你将被曝光
| 签名 | 描述 | 分数 | 严重性 |
|---|---|---|---|
| UA bot: curl | 检测到已知机器人/爬虫的User-Agent | +40 | |
| Danger medium hits: 1 | 中等风险:管理面板、配置文件 | +10 |
从服务器访问日志重建的HTTP请求。出于安全考虑,目标域名已隐藏。
* Typical request patterns for detected signatures. Actual target domains are redacted.
IP 104.207.36.192显示可疑的UA行为。阻止空User-Agent请求。为敏感端点实施基于JavaScript的机器人检测。
来自同一/24子网的其他被封锁IP——表明该网络范围存在系统性滥用。
来自Shodan的网络侦察数据。开放端口可能表示正在运行的服务、错误配置或潜在的攻击面。
| Port | Service | Risk | Description |
|---|---|---|---|
| 22 | SSH | Low | Secure Shell — common brute force target for remote access |
| 179 | Unknown | Low | Service on port 179 |
| 1080 | Unknown | Low | Service on port 1080 |
| 3128 | Unknown | Low | Service on port 3128 |
| 3129 | Unknown | Low | Service on port 3129 |
| 8081 | Unknown | Low | Service on port 8081 |
数据来源:Shodan InternetDB。独立于abuse.mom进行扫描。
该IP已通过全球邮件服务器和防火墙使用的主要DNS黑名单进行检查。
已检查:Spamhaus、SpamCop、Barracuda、SORBS、CBL、UCEProtect。
104.207.36.192 has been assigned a threat score of 50/100 (Medium). 该IP呈现中等风险。建议对来自此地址的流量实施速率限制和增强日志记录。
The following attack categories were identified:
我们的监控基础设施已将104.207.36.192(地理位置为Ashburn, United States,运营在3xK Tech GmbH的网络中)识别为可疑网络活动的来源。 在1天的时间内,此IP产生了1次恶意请求,平均每天约1次请求。 从住宅网络运营,此IP可能代表一个被入侵的家庭网关或已被招募到更大攻击基础设施中的IoT设备。 检测到可疑的User-Agent异常,包括空的、伪造的或快速轮换的UA字符串——自动化扫描工具的特征。 我们的记录显示来自United States的157个恶意IP,使其成为全球威胁活动的重要贡献者。 评分50/100需要主动监控和速率限制。建议对敏感系统进行完全封锁。
This IP is classified as residential, suggesting it may belong to a compromised home device, IoT botnet member, or an infected personal computer. Residential IPs involved in attacks often indicate malware infection without the owner's knowledge.
Examining HTTP headers beyond User-Agent reveals attack tools and automated scripts. Missing standard headers, unusual ordering, non-standard values, and inconsistencies with claimed client identity all serve as reliable detection signals.
Threat scoring combines multiple signals — request patterns, known signatures, IP reputation, geographic risk, and behavioral analysis — into a single actionable metric. Weighted scoring models allow tuning sensitivity to balance security with usability.