
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 | |
| UA changed for same IP | Multiple User-Agents — bot rotation technique | +25 | |
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Danger strong hits: 1 | High-risk paths: shells, RCE vectors, exploits | +25 | |
| Danger strong hits: 14 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Burst: 18 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 61 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| 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 | |
| Burst: 62 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 17 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 60 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Foreign referer seen | Referer from unrelated external domain | +10 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Address UA spoofing from 209.87.169.138: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
IP 209.87.169.138 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
IP 209.87.169.138 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.
209.87.169.138 has been assigned a threat score of 255/100 (Critical). A score this high marks a critical threat actor. This address has demonstrated persistent, aggressive malicious behavior across multiple detection vectors.
The following attack categories were identified:
IP address 209.87.169.138 has been traced to Jersey City, United States, operating on the network of Internet Utilities NA LLC. Our threat detection systems have flagged this address based on observed malicious behavior patterns. During its 56-day observation window, we recorded 11 hostile requests from this IP — roughly 0.2 per day on average. This residential IP is likely a compromised consumer device. Home routers and IoT equipment with default credentials are prime targets for botnet operators. The diversity of 3 separate attack methods suggests a comprehensive attack toolkit — likely an automated scanner that tests for vulnerabilities across multiple categories. 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.
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.
IP geolocation databases provide approximate locations with varying accuracy. City-level geolocation is typically 50-80% accurate, while country-level exceeds 95%. VPNs, proxies, and mobile networks further reduce reliability, making geolocation a useful but imperfect intelligence signal.