
ABUSE.MOM — 规矩点,否则你将被曝光
| 签名 | 描述 | 分数 | 严重性 |
|---|---|---|---|
| Burst 5/2s | 请求频率异常——自动扫描 | +35 | |
| Burst: 5 req / 2s | 请求频率异常——自动扫描 | +35 | |
| 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 | |
| Form spam: no_js_check | 请求内容中的垃圾/恶意关键词 | +0 | |
| 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 | |
| spam:no_js_check | 请求内容中的垃圾/恶意关键词 | +0 |
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77.238.253.153。
在所有公共表单上启用CAPTCHA。添加蜜罐字段。将每个IP的提交限制为每分钟3次。部署Akismet或CleanTalk。
IP 77.238.253.153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。
77.238.253.153 has been assigned a threat score of 100/100 (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:
IP地址77.238.253.153已追溯至Amsterdam, Netherlands,运营在Servers Tech Fzco的网络中。我们的威胁检测系统根据观察到的恶意行为模式标记了此地址。 我们的传感器在35天内捕获了来自此地址的2,620次恶意请求,反映出每天约74.9次的持续攻击节奏。 该IP被归类为托管/数据中心基础设施,通常与用于自动化攻击活动、僵尸网络命令控制或大规模漏洞扫描的租用服务器相关联。 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。 我们的记录显示来自Netherlands的178个恶意IP,使其成为全球威胁活动的重要贡献者。 评分100/100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.
CAPTCHAs remain a primary bot defense but face increasing bypass rates from AI-powered solvers. Modern alternatives include invisible behavioral analysis, proof-of-work challenges, and device fingerprinting that detect bots without impacting user experience.