
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Form spam: no_js_check | Spam/malware keywords in request content | +0 | |
| UA suspicious (short/empty) | Behavioral anomaly detected by automated analysis | +15 | |
| 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 changed for same IP | Multiple User-Agents — bot rotation technique | +25 | |
| Danger strong hits: 394 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 927 | Medium-risk: admin panels, config files | +60 | |
| Burst: 36 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 126 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 140 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 367 | Medium-risk: admin panels, config files | +60 | |
| Burst: 34 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 117 req / 10s | Abnormally fast request rate — automated scanning | +35 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Enable CAPTCHA on all public forms. Add honeypot fields. Rate-limit submissions to 3 per minute per IP. Deploy Akismet or CleanTalk.
Address UA spoofing from 31.171.130.76: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
Block scanning from 31.171.130.76: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
IP 31.171.130.76 is generating excessive traffic. Limit connections per source IP. Enable geographic blocking if traffic from this region is unexpected.
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
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.
31.171.130.76 has been assigned a threat score of 255/100 (Critical). This represents a critical risk level. Our detection systems have flagged multiple high-confidence indicators of malicious intent from this address.
The following attack categories were identified:
31.171.130.76 is registered in Slough, United Kingdom, operating on the network of F.N.S. HOLDINGS LIMITED. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. Our sensors captured 5 malicious requests from this address across a 63-day span, reflecting a sustained attack cadence of ~0.1 requests per day. The address operates as a VPN/proxy exit node. Attackers route traffic through anonymizing services to obscure their real location and evade IP-based security controls. The combination of 3 distinct attack vectors indicates a sophisticated, multi-pronged threat actor deploying automated tools that probe multiple attack surfaces simultaneously. United Kingdom currently accounts for 132 blocked IPs in our database, making it a significant source of malicious traffic. At 255/100, this is an extremely high-risk address. All traffic should be considered hostile.
This IP is associated with a VPN or proxy service. Attackers frequently route their traffic through anonymizing services to obscure their true location. This makes attribution more challenging but the malicious behavior patterns remain detectable.
SQL injection remains one of the most common web attack vectors. Attackers inject malicious SQL code through input fields to extract database contents, modify data, or gain administrative access. Automated scanners test for SQLi vulnerabilities at massive scale.
Modern attacks increasingly target APIs rather than traditional web interfaces. Attackers enumerate endpoints, test for broken authentication, and exploit excessive data exposure. API attacks are harder to detect as they mimic legitimate programmatic access patterns.