
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger medium hits: 4 | Medium-risk: admin panels, config files | +40 | |
| POST seen | Behavioral anomaly detected by automated analysis | +8 | |
| UA changed | Multiple User-Agents — bot rotation technique | +25 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
IP 49.36.9.163 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
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.
49.36.9.163 has been assigned a threat score of 73/100 (High). This score indicates high threat severity. The IP has shown clear patterns of malicious behavior that warrant immediate defensive measures.
The following attack categories were identified:
Our monitoring infrastructure has identified 49.36.9.163, geolocated to Mumbai, India, operating on the network of Reliance Jio Infocomm Limited, as a source of suspicious network activity. The address has been active for 5 days in our monitoring system, producing 161 flagged requests at a rate of ~32.2/day. This is a mobile network IP. While mobile addresses are typically shared via CGNAT, persistent malicious activity from this specific address suggests automated abuse. Detected suspicious User-Agent anomalies including empty, forged, or rapidly rotating UA strings — characteristic of automated scanning tools. With 201 flagged addresses, India represents a significant presence in our threat database. A threat score of 73/100 places this IP in the high-risk category. Blocking at the firewall level is recommended.
Path traversal attacks attempt to access files outside the intended directory by manipulating file path references. Attackers use sequences like ../ to reach sensitive system files such as /etc/passwd or application configuration files.
Threat scoring combines multiple signals — request patterns, known signatures, IP reputation, geographic risk, and behavioral analysis — into a single actionable metric. Weighted scoring models allow tuning sensitivity to balance security with usability.