
ABUSE.MOM — 规矩点,否则你将被曝光
| 签名 | 描述 | 分数 | 严重性 |
|---|---|---|---|
| 404 ratio 40-60% | 大多数请求返回404——目录枚举 | +15 | |
| Burst 6/2s | 请求频率异常——自动扫描 | +35 | |
| Danger medium hits: 2 | 中等风险:管理面板、配置文件 | +20 | |
| Danger strong hits: 2 | 高风险路径:Webshell、RCE、漏洞利用 | +50 | |
| POST seen | 自动分析检测到行为异常 | +8 | |
| Probe 302→404 | 自动分析检测到行为异常 | +20 | |
| UA changed | 多个User-Agent——机器人轮换技术 | +25 | |
| UA suspicious | 自动分析检测到行为异常 | +15 |
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 138.68.176.103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。
在nginx中实施limit_req_zone。部署具有DDoS防护的CDN。配置SYN cookies和连接跟踪以限制138.68.176.103。
IP 138.68.176.103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。
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。
138.68.176.103 has been assigned a threat score of 158/100 (Critical). 这代表着极高风险等级。我们的检测系统已从该地址标记出多个高置信度的恶意意图指标。
The following attack categories were identified:
138.68.176.103注册在Slough, United Kingdom,运营在DigitalOcean, LLC的网络中。该IP在触发多个行为检测签名后首次出现在我们的威胁源中。 我们的传感器在1天内捕获了来自此地址的77次恶意请求,反映出每天约77次的持续攻击节奏。 被归类为托管IP,此地址可能运行在租用的服务器或云实例上。攻击者偏好数据中心IP因其高带宽和一次性特点。 检测到3种不同攻击模式,此IP表现出高级自动化扫描框架的典型行为特征。 威胁评分158/100,此IP属于我们数据库中最危险的地址之一。强烈建议立即完全封锁。
This IP belongs to a hosting or data center provider. Malicious traffic from hosting infrastructure often originates from compromised VPS instances, rented servers used for scanning campaigns, or abused free-tier cloud accounts. Hosting providers typically respond to abuse reports within 24-72 hours.
Distributed denial of service attacks overwhelm infrastructure with traffic volume. Effective mitigation combines always-on traffic scrubbing, anycast network distribution, rate limiting, and the ability to quickly scale absorption capacity during attacks.
WAFs inspect HTTP traffic to block common attacks but require careful tuning. Overly aggressive rules cause false positives while permissive configurations miss attacks. Modern WAFs combine signature matching with behavioral analysis and machine learning.