IP Threat Report
212.30.36.140
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 | |
| Danger medium hits: 1 | Medium-risk: admin panels, config files | +10 | |
| Danger medium hits: 2 | Medium-risk: admin panels, config files | +20 | |
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| Foreign referer | Referer from unrelated external domain | +10 | |
| Foreign referer seen | Referer from unrelated external domain | +10 | |
| UA changed | Multiple User-Agents — bot rotation technique | +25 | |
| UA changed for same IP | 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
Network Provider
Recommendations
Actions taken & recommended
- IP 212.30.36.140 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 212.30.36.0/24
- Report abuse to the network provider via their abuse contact
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
🔎 Path Enumeration Protection
Block scanning from 212.30.36.140: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
🤖 Bot Detection
Address UA spoofing from 212.30.36.140: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
Neighbors in 212.30.36.0/24
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
212.30.36.140 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.
The following attack categories were identified:
📊 Threat Analysis
212.30.36.140 is registered in Nuremberg, Germany, operating on the network of GSL Networks Pty LTD. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. The address has been active for 10 days in our monitoring system, producing 741 flagged requests at a rate of ~74.1/day. This is a residential IP address, suggesting a compromised home device such as a router, smart appliance, or infected workstation participating in a botnet. Two attack patterns were identified (Path Enumeration and User-Agent Anomaly), suggesting a semi-automated campaign that targets multiple vulnerabilities. Our records show 151 malicious IPs originating from Germany, positioning it as a significant contributor to global threat activity. A score of 100/100 places this address in the top tier of severity. Block and investigate any historical connections.
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.
Related Threats
Security Intelligence
💡 HTTP Request Smuggling
Request smuggling exploits differences in how front-end and back-end servers parse HTTP requests. This technique can bypass security controls, poison web caches, and hijack other users sessions by desynchronizing request boundaries.
💡 False Positive Management
False positives erode trust in security systems and waste analyst resources. Effective management requires feedback loops, allowlisting mechanisms, contextual analysis, and regular tuning of detection rules based on operational experience.