
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA changed for same IP | Multiple User-Agents — bot rotation technique | +25 | |
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| Danger medium hits: 1 | Medium-risk: admin panels, config files | +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 37.140.223.132: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
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.
37.140.223.132 has been assigned a threat score of 85/100 (Critical). With this rating, the IP falls into the critical severity bracket — among the most dangerous addresses in our monitoring database.
The following attack categories were identified:
Network traffic from 37.140.223.132, located in Los Angeles, United States, operating on the network of F.N.S. HOLDINGS LIMITED, has been classified as malicious by our automated threat scoring engine. During its 1-day observation window, we recorded 1 hostile requests from this IP — roughly 1 per day on average. This residential IP is likely a compromised consumer device. Home routers and IoT equipment with default credentials are prime targets for botnet operators. The IP exhibits User-Agent manipulation, switching between different browser identities or sending empty headers. Our records show 151 malicious IPs originating from United States, positioning it as a significant contributor to global threat activity. At 85/100, this IP warrants immediate defensive action.
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.
CDNs can inadvertently mask the true origin of malicious traffic, making attribution difficult. Attackers abuse CDN services to proxy their attacks, leverage cached content for amplification, and exploit misconfigurations in CDN-to-origin connections.