IP Threat Report
212.30.33.72
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA bot: python | Known bot/crawler User-Agent detected | +40 | |
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| Danger medium hits: 1 | Medium-risk: admin panels, config files | +10 | |
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| UA bot: Go-http-client | Known bot/crawler User-Agent detected | +40 | |
| Danger strong hits: 73 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 277 | Medium-risk: admin panels, config files | +60 | |
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 | |
| Burst: 7 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 25 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Foreign referer seen | Referer from unrelated external domain | +10 | |
| UA changed for same IP | Multiple User-Agents — bot rotation technique | +25 | |
| Danger strong hits: 14 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Burst: 13 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 46 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 1 | High-risk paths: shells, RCE vectors, exploits | +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 212.30.33.72 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 212.30.33.0/24
- Report abuse to the network provider via their abuse contact
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
🤖 Bot Detection
Address UA spoofing from 212.30.33.72: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
🔎 Path Enumeration Protection
Block scanning from 212.30.33.72: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
🌊 Flood / DDoS Mitigation
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 212.30.33.72.
Neighbors in 212.30.33.0/24
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
212.30.33.72 has been assigned a threat score of 305/100 (Critical). This is a critical-level threat. Systems administrators should treat this IP as hostile and block all inbound connections without exception.
The following attack categories were identified:
📊 Threat Analysis
The address 212.30.33.72 originates from Madrid, Spain, operating on the network of Datacamp Limited. It was identified through automated analysis of incoming network traffic across monitored endpoints. The address has been active for 53 days in our monitoring system, producing 4 flagged requests at a rate of ~0.1/day. The address is classified as residential, meaning it likely belongs to an end-user ISP connection. Malicious activity from residential IPs typically indicates device compromise or botnet membership. With 3 different attack patterns detected, this IP exhibits behavior characteristic of advanced automated scanning frameworks. With a threat score of 305/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly recommended.
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
💡 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.
💡 SSH Brute Force Defense
SSH servers face constant brute force attacks targeting common usernames and weak passwords. Key-based authentication, fail2ban, non-standard ports, and IP allowlisting dramatically reduce the attack surface. Monitoring auth logs reveals active campaigns and compromised credentials.