
ABUSE.MOM — 规矩点,否则你将被曝光
| 签名 | 描述 | 分数 | 严重性 |
|---|---|---|---|
| Burst 200/10s | 请求频率异常——自动扫描 | +35 | |
| Burst 67/2s | 请求频率异常——自动扫描 | +35 | |
| Burst: 200 req / 10s | 请求频率异常——自动扫描 | +35 | |
| Burst: 67 req / 2s | 请求频率异常——自动扫描 | +35 | |
| Danger medium hits: 502 | 中等风险:管理面板、配置文件 | +60 | |
| Danger strong hits: 502 | 高风险路径:Webshell、RCE、漏洞利用 | +100 | |
| Foreign referer | 来自无关外部域名的Referer | +10 | |
| Foreign referer seen | 来自无关外部域名的Referer | +10 | |
| POST requests present | 自动分析检测到行为异常 | +8 | |
| POST seen | 自动分析检测到行为异常 | +8 | |
| UA changed | 多个User-Agent——机器人轮换技术 | +25 | |
| UA changed for same IP | 多个User-Agent——机器人轮换技术 | +25 |
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.
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64.226.94.117。
IP 64.226.94.117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。
64.226.94.117 has been assigned a threat score of 273/100 (Critical). 这是一个严重级别的威胁。系统管理员应将此IP视为敌对地址,无例外地阻止所有入站连接。
The following attack categories were identified:
64.226.94.117注册在Frankfurt am Main, Germany,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。 在其5天的观察窗口期间,我们记录了来自此IP的165次敌对请求——平均每天约33次。 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。 识别出两种攻击模式(Request Flooding和User-Agent Anomaly),表明这是一个针对多个漏洞的半自动化攻击活动。 评分273/100将此地址置于最高严重性级别。应封锁并调查任何历史连接。
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.
GraphQL APIs introduce specific vulnerabilities including introspection information disclosure, query complexity attacks, batching abuse, and authorization bypass through nested queries. Depth limiting, cost analysis, and field-level authorization address these GraphQL-specific threats.