
ABUSE.MOM — 规矩点,否则你将被曝光
| 签名 | 描述 | 分数 | 严重性 |
|---|---|---|---|
| Danger strong hits: 2 | 高风险路径:Webshell、RCE、漏洞利用 | +50 | |
| Burst: 5 req / 2s | 请求频率异常——自动扫描 | +35 | |
| Foreign referer seen | 来自无关外部域名的Referer | +10 | |
| Burst: 25 req / 2s | 请求频率异常——自动扫描 | +35 | |
| Burst: 28 req / 10s | 请求频率异常——自动扫描 | +35 |
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64.50.191.32。
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 |
|---|---|---|---|
| 25 | SMTP | Medium | SMTP mail server — can be abused for spam relay |
| 80 | HTTP | Low | HTTP web server — standard web traffic |
| CVE ID | Link |
|---|---|
| CVE-2019-11047 | NVD → |
| CVE-2019-11050 | NVD → |
| CVE-2022-31628 | NVD → |
| CVE-2020-7059 | NVD → |
| CVE-2020-7067 | NVD → |
| CVE-2024-25117 | NVD → |
| CVE-2022-31629 | NVD → |
| CVE-2020-7060 | NVD → |
| CVE-2017-8923 | NVD → |
| CVE-2019-11048 | NVD → |
| CVE-2020-7063 | NVD → |
| CVE-2019-11046 | NVD → |
| CVE-2022-4900 | NVD → |
| CVE-2020-7069 | NVD → |
| CVE-2019-11045 | NVD → |
| CVE-2024-3566 | NVD → |
| CVE-2020-7070 | NVD → |
| CVE-2020-7061 | NVD → |
| CVE-2019-11044 | NVD → |
| CVE-2020-7062 | NVD → |
| CVE-2007-3205 | NVD → |
| CVE-2020-7068 | NVD → |
| CVE-2020-7064 | NVD → |
| CVE-2022-37454 | NVD → |
| CVE-2013-2220 | NVD → |
🔴 此主机有26个已知CVE与其暴露的服务相关联。如此大量的漏洞强烈表明软件严重过时。 请在NVD数据库中查看每个CVE的详细信息。
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。
64.50.191.32 has been assigned a threat score of 130/100 (Critical). 凭借此评分,该IP属于严重威胁级别——是我们监控数据库中最危险的地址之一。
The following attack categories were identified:
我们的监控基础设施已将64.50.191.32(地理位置为Los Angeles, United States,运营在BreezeHost的网络中)识别为可疑网络活动的来源。 我们的传感器在23天内捕获了来自此地址的14次恶意请求,反映出每天约0.6次的持续攻击节奏。 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。 来自此IP的基于速率的攻击旨在通过大量请求洪水压垮服务器资源。 评分130/100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 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.
Signature-based detection matches known attack patterns but misses novel threats. Behavioral analysis identifies anomalies in request patterns, timing, and volume, catching zero-day attacks that signatures cannot recognize.