IP Threat Report
165.227.170.185
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 165.227.170.185 is blocked at application level (HTTP 403)
- Consider blocking at firewall level (iptables/CSF) to reduce server load
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
⚙️ Defensive Recommendations
Block 165.227.170.185 at the network perimeter. Implement defense-in-depth combining IP blocking with application-layer protections.
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
165.227.170.185 has been assigned a threat score of 120/100 (Critical). This places it in the critical threat category. Immediate blocking is strongly advised across all network perimeters.
📊 Threat Analysis
The address 165.227.170.185 originates from Frankfurt am Main, Germany, operating on the network of DigitalOcean, LLC. It was identified through automated analysis of incoming network traffic across monitored endpoints. Our sensors captured 419 malicious requests from this address across a 5-day span, reflecting a sustained attack cadence of ~83.8 requests per day. Germany currently accounts for 101 blocked IPs in our database, making it a significant source of malicious traffic. With a threat score of 120/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly recommended.
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💡 Mobile Network Threat Landscape
Mobile carrier NAT (CGNAT) means thousands of users share a single public IP, making mobile IPs unreliable for reputation scoring. However, mobile networks are increasingly used as attack platforms through compromised apps and malicious SDKs.
💡 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.