
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.
IP 31.171.130.123 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
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.
31.171.130.123 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:
31.171.130.123 is registered in Slough, United Kingdom, operating on the network of F.N.S. HOLDINGS LIMITED. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. The address has been active for 1 days in our monitoring system, producing 1 flagged requests at a rate of ~1/day. This IP is identified as a VPN or proxy endpoint, commonly used to mask the true origin of attack traffic and bypass geographic or reputation-based blocking. Detected suspicious User-Agent anomalies including empty, forged, or rapidly rotating UA strings — characteristic of automated scanning tools. Our records show 145 malicious IPs originating from United Kingdom, positioning it as a significant contributor to global threat activity. At 85/100, this IP warrants immediate defensive action.
This IP is associated with a VPN or proxy service. Attackers frequently route their traffic through anonymizing services to obscure their true location. This makes attribution more challenging but the malicious behavior patterns remain detectable.
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.
Analyzing User-Agent strings reveals automated tools masquerading as legitimate browsers. Inconsistencies between claimed browser capabilities and actual behavior, impossible version combinations, and known scanner signatures help identify malicious clients.