
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA changed for same IP | Multiple User-Agents — bot rotation technique | +25 | |
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Burst: 5 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 10 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Foreign referer seen | Referer from unrelated external domain | +10 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Address UA spoofing from 8.211.41.107: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
IP 8.211.41.107 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 8.211.41.107.
Network reconnaissance data from Shodan. Open ports may indicate running services, misconfigurations, or potential attack surfaces.
| Port | Service | Risk | Description |
|---|---|---|---|
| 22 | SSH | Low | Secure Shell — common brute force target for remote access |
| CVE ID | Link |
|---|---|
| CVE-2020-14145 | NVD → |
| CVE-2023-51767 | NVD → |
| CVE-2025-26465 | NVD → |
| CVE-2023-51385 | NVD → |
| CVE-2023-38408 | NVD → |
| CVE-2008-3844 | NVD → |
| CVE-2007-2768 | NVD → |
| CVE-2016-20012 | NVD → |
| CVE-2018-15473 | NVD → |
| CVE-2018-20685 | NVD → |
| CVE-2023-48795 | NVD → |
| CVE-2025-32728 | NVD → |
| CVE-2021-41617 | NVD → |
| CVE-2020-15778 | NVD → |
| CVE-2019-6109 | NVD → |
| CVE-2018-15919 | NVD → |
| CVE-2021-36368 | NVD → |
| CVE-2019-6111 | NVD → |
| CVE-2017-15906 | NVD → |
| CVE-2019-6110 | NVD → |
🔴 This host has 20 known CVEs associated with its exposed services. This volume strongly suggests severely outdated software. Review each CVE in the NVD database.
Data source: Shodan InternetDB. Scanned independently of abuse.mom.
This IP was checked against major DNS-based blacklists used by mail servers and firewalls worldwide.
Checked: Spamhaus, SpamCop, Barracuda, SORBS, CBL, UCEProtect. Results may change over time.
8.211.41.107 has been assigned a threat score of 120/100 (Critical). This is a critical-level threat. Systems administrators should treat this IP as hostile and block all inbound connections without exception.
The following attack categories were identified:
8.211.41.107 is registered in Frankfurt am Main, Germany, operating on the network of Alibaba (US) Technology Co., Ltd.. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. During its 1-day observation window, we recorded 1 hostile requests from this IP — roughly 1 per day on average. The address is classified as residential, meaning it likely belongs to an end-user ISP connection. Malicious activity from residential IPs typically indicates device compromise or botnet membership. The combination of 3 distinct attack vectors indicates a sophisticated, multi-pronged threat actor deploying automated tools that probe multiple attack surfaces simultaneously. With 102 flagged addresses, Germany represents a significant presence in our threat database. With a threat score of 120/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly recommended.
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.
TLS fingerprinting creates unique identifiers based on how clients negotiate encrypted connections. The JA3 and JA4 methods generate hashes from TLS ClientHello parameters, enabling identification of specific tools and malware regardless of IP address changes.
Artificial intelligence enables more convincing phishing content, faster vulnerability discovery, and adaptive attack strategies that learn from defensive responses. AI-generated social engineering and automated exploit development represent growing threats.