
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA bot: python | Known bot/crawler User-Agent detected | +40 | |
| Danger strong hits: 1 | High-risk paths: shells, RCE vectors, exploits | +25 |
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 45.154.138.52: 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.
45.154.138.52 has been assigned a threat score of 65/100 (High). At this threat level, the IP is considered high risk. Firewall rules should be updated to deny traffic from this source.
The following attack categories were identified:
Network traffic from 45.154.138.52, located in Marseille, France, operating on the network of F.N.S. HOLDINGS LIMITED, has been classified as malicious by our automated threat scoring engine. 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. The IP exhibits User-Agent manipulation, switching between different browser identities or sending empty headers. Our records show 146 malicious IPs originating from France, positioning it as a significant contributor to global threat activity. At 65/100, this IP presents a meaningful threat. Implement rate limiting with escalation to blocking.
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.
Internet traffic routing through a limited number of submarine cables and exchange points creates natural chokepoints. Understanding these routing patterns helps explain geographic clustering of certain attack types and latency-based scanning behaviors.