IP Threat Report
31.162.31.183
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA changed for same IP | Multiple User-Agents — bot rotation technique | +25 | |
| Foreign referer seen | Referer from unrelated external domain | +10 | |
| Form spam: no_js_check | Spam/malware keywords in request content | +0 | |
| Burst: 12 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 12 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 6 req / 2s | Abnormally fast request rate — automated scanning | +35 |
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 31.162.31.183 is blocked at application level (HTTP 403)
- Consider blocking at firewall level (iptables/CSF) to reduce server load
- Report abuse to the network provider via their abuse contact
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
🤖 User-Agent Anomaly Defense
IP 31.162.31.183 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
📧 Spam Protection
Enable CAPTCHA on all public forms. Add honeypot fields. Rate-limit submissions to 3 per minute per IP. Deploy Akismet or CleanTalk.
🌊 Traffic Flood Defense
IP 31.162.31.183 is generating excessive traffic. Limit connections per source IP. Enable geographic blocking if traffic from this region is unexpected.
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
31.162.31.183 has been assigned a threat score of 95/100 (Critical). With this rating, the IP falls into the critical severity bracket — among the most dangerous addresses in our monitoring database.
The following attack categories were identified:
📊 Threat Analysis
Network traffic from 31.162.31.183, located in Perm, Russia, operating on the network of OJSC uralsvyazinform, has been classified as malicious by our automated threat scoring engine. Our sensors captured 9 malicious requests from this address across a 3-day span, reflecting a sustained attack cadence of ~3 requests per day. This residential IP is likely a compromised consumer device. Home routers and IoT equipment with default credentials are prime targets for botnet operators. The dual attack vectors of User-Agent Anomaly combined with Request Flooding indicate a coordinated assault rather than opportunistic scanning. With 190 flagged addresses, Russia represents a significant presence in our threat database. At 95/100, this is an extremely high-risk address. All traffic should be considered hostile.
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
💡 User-Agent Analysis Techniques
Analyzing User-Agent strings reveals automated tools masquerading as legitimate browsers. Inconsistencies between claimed browser capabilities and actual behavior, impossible version combinations, and known scanner signatures help identify malicious clients.
💡 Phishing Infrastructure Analysis
Modern phishing operations use sophisticated infrastructure including lookalike domains, valid TLS certificates, and evasion techniques like cloaking and geofencing. Analyzing this infrastructure reveals campaigns before they reach their targets.