IP Threat Report
162.141.167.50
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| UA changed | Multiple User-Agents — bot rotation technique | +25 |
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 162.141.167.50 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 162.141.167.0/24
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
🤖 Bot Detection
Address UA spoofing from 162.141.167.50: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
Neighbors in 162.141.167.0/24
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
162.141.167.50 has been assigned a threat score of 75/100 (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:
📊 Threat Analysis
Threat intelligence analysis has linked 162.141.167.50 to malicious activity originating from an unknown location. The address has been under observation since its initial detection. The address has been active for 1 days in our monitoring system, producing 8 flagged requests at a rate of ~8/day. The IP exhibits User-Agent manipulation, switching between different browser identities or sending empty headers. The score of 75/100 indicates a confirmed malicious actor. Network-level blocking is appropriate.
Related Threats
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💡 File Upload Vulnerabilities
Insecure file upload functionality allows attackers to upload web shells, malware, or scripts that execute on the server. Proper validation must check file content, not just extensions, and uploaded files should be stored outside the web root.
💡 Machine Learning in Threat Detection
Machine learning models analyze vast amounts of network traffic to identify attack patterns invisible to rule-based systems. Supervised models classify known attack types while unsupervised models detect anomalies that may indicate novel threats.