
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA bot: crawler | Known bot/crawler User-Agent detected | +40 | |
| 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 57.141.20.1: 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.
57.141.20.1 has been assigned a threat score of 50/100 (Medium). The address carries a moderate risk rating. Defensive monitoring is advised, with escalation to blocking if activity intensifies.
The following attack categories were identified:
57.141.20.1 is registered in New York, United States, operating on the network of Facebook, Inc.. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. During its 25-day observation window, we recorded 9 hostile requests from this IP — roughly 0.4 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 IP exhibits User-Agent manipulation, switching between different browser identities or sending empty headers. Our records show 199 malicious IPs originating from United States, positioning it as a significant contributor to global threat activity. At 50/100, this IP presents a meaningful threat. Implement rate limiting with escalation to blocking.
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.
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.
Network telescopes monitor large blocks of unused IP address space. Since no legitimate traffic should reach these addresses, all observed traffic represents scanning, backscatter from spoofed attacks, or misconfiguration — providing pure signal for threat analysis.