
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.
IP 57.141.0.72 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.
57.141.0.72 has been assigned a threat score of 50/100 (Medium). This is a moderate threat. While not the most dangerous, this IP shows patterns that warrant monitoring and potential rate-limiting.
The following attack categories were identified:
The address 57.141.0.72 originates from Ashburn, United States, operating on the network of Facebook, Inc.. It was identified through automated analysis of incoming network traffic across monitored endpoints. During its 21-day observation window, we recorded 15 hostile requests from this IP — roughly 0.7 per day on average. Operating from a residential network, this IP may represent a compromised home gateway or IoT device that has been drafted into a larger attack infrastructure. Detected suspicious User-Agent anomalies including empty, forged, or rapidly rotating UA strings — characteristic of automated scanning tools. United States currently accounts for 199 blocked IPs in our database, making it a significant source of malicious traffic. The score of 50/100 warrants active monitoring and rate-limiting. Full blocking is advisable for sensitive systems.
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.
Open redirect vulnerabilities allow attackers to redirect users from trusted domains to malicious sites. While often underestimated, these flaws enable convincing phishing, token theft through redirect-based OAuth flows, and SSRF chains.