
ABUSE.MOM — 规矩点,否则你将被曝光
| 签名 | 描述 | 分数 | 严重性 |
|---|---|---|---|
| Danger strong hits: 1 | 高风险路径:Webshell、RCE、漏洞利用 | +25 | |
| Danger medium hits: 1 | 中等风险:管理面板、配置文件 | +10 | |
| 404 ratio >= 60% | 大多数请求返回404——目录枚举 | +25 | |
| POST requests present | 自动分析检测到行为异常 | +8 |
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 154.16.105.35正在枚举目录。在10次以上404错误后配置fail2ban apache-404 jail。禁用目录列表。
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 |
|---|---|---|---|
| 1337 | Unknown | Low | Service on port 1337 |
| 6443 | Unknown | Low | Service on port 6443 |
| 8080 | HTTP-Alt | Low | HTTP alternative port — often used for admin panels or proxies |
| 8081 | Unknown | Low | Service on port 8081 |
| 8443 | HTTPS-Alt | Low | Service on port 8443 |
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。
154.16.105.35 has been assigned a threat score of 68/100 (High). 在此威胁级别下,该IP被视为高风险。应更新防火墙规则以拒绝来自此来源的流量。
The following attack categories were identified:
威胁情报分析将154.16.105.35与来自Las Vegas, United States,运营在Cogent Communications的网络中的恶意活动相关联。该地址自首次检测以来一直处于观察状态。 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。 这是一个住宅IP地址,表明可能是被入侵的家用设备,如路由器、智能设备或参与僵尸网络的受感染工作站。 该IP表现出目录枚举行为,系统地请求不存在的路径以发现隐藏文件和配置错误的资源。 我们的记录显示来自United States的186个恶意IP,使其成为全球威胁活动的重要贡献者。 评分68/100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.
Credential stuffing uses stolen username-password pairs from data breaches to attempt logins across many websites. Since users frequently reuse passwords, these automated attacks achieve success rates of 0.1-2%, which translates to thousands of compromised accounts from millions of attempts.
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.