IP Threat Report
37.140.223.63
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| Directory Scan | Behavioral anomaly detected by automated analysis | +0 |
Observed Activity
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Timeline
Recommendations
Actions taken & recommended
- IP 37.140.223.63 is blocked at application level (HTTP 403)
- Consider blocking at firewall level (iptables/CSF) to reduce server load
- Other malicious IPs detected in the same /24 subnet — consider blocking 37.140.223.0/24
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
⚙️ Defensive Recommendations
Block 37.140.223.63 at the network perimeter. Implement defense-in-depth combining IP blocking with application-layer protections.
Neighbors in 37.140.223.0/24
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
Blacklist Status (DNSBL)
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.
Threat Analysis
37.140.223.63 has been assigned a threat score of 100/100 (Critical). This places it in the critical threat category. Immediate blocking is strongly advised across all network perimeters.
📊 Threat Analysis
Our monitoring infrastructure has identified 37.140.223.63, geolocated to Los Angeles, United States, operating on the network of F.N.S. HOLDINGS LIMITED, as a source of suspicious network activity. The address has been active for 11 days in our monitoring system, producing 76 flagged requests at a rate of ~6.9/day. With 150 flagged addresses, United States represents a significant presence in our threat database. At 100/100, this is an extremely high-risk address. All traffic should be considered hostile.
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💡 TLS Fingerprinting (JA3/JA4)
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.
💡 HTTP Header Analysis for Threat Detection
Examining HTTP headers beyond User-Agent reveals attack tools and automated scripts. Missing standard headers, unusual ordering, non-standard values, and inconsistencies with claimed client identity all serve as reliable detection signals.