
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| 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 | |
| Danger strong hits: 1 | High-risk paths: shells, RCE vectors, exploits | +25 | |
| UA changed for same IP | Multiple User-Agents — bot rotation technique | +25 | |
| Danger strong hits: 127 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 50 | Medium-risk: admin panels, config files | +60 | |
| Burst: 20 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 68 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 47 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Burst: 19 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 60 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 378 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 970 | Medium-risk: admin panels, config files | +60 | |
| Burst: 22 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 77 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 67 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 17 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 62 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 55 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Burst: 18 req / 2s | 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.
IP 209.87.169.130 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
IP 209.87.169.130 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 209.87.169.130.
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.
209.87.169.130 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:
209.87.169.130 is registered in Jersey City, United States, operating on the network of Internet Utilities NA LLC. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. During its 50-day observation window, we recorded 11 hostile requests from this IP — roughly 0.2 per day on average. This is a residential IP address, suggesting a compromised home device such as a router, smart appliance, or infected workstation participating in a botnet. The combination of 3 distinct attack vectors indicates a sophisticated, multi-pronged threat actor deploying automated tools that probe multiple attack surfaces simultaneously. With 217 flagged addresses, United States represents a significant presence in our threat database. At 255/100, 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.
Examining HTTP headers beyond User-Agent reveals attack tools and automated scripts. Missing standard headers, unusual ordering, non-standard values, and inconsistencies with claimed client identity all serve as reliable detection signals.
Effective rate limiting must balance protection against abuse with allowing legitimate traffic bursts. Sliding window algorithms, token buckets, and adaptive thresholds based on client reputation provide layered defense against flooding attacks.