
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Directory Scan | Behavioral anomaly detected by automated analysis | +0 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Block 209.163.117.172 at the network perimeter. Implement defense-in-depth combining IP blocking with application-layer protections.
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.
209.163.117.172 has been assigned a threat score of 95/100 (Critical). This places it in the critical threat category. Immediate blocking is strongly advised across all network perimeters.
209.163.117.172 is registered in Chicago, United States, operating on the network of Emeigh Investments LLC. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. During its 2-day observation window, we recorded 421 hostile requests from this IP — roughly 210.5 per day on average. 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. United States currently accounts for 128 blocked IPs in our database, making it a significant source of malicious traffic. A score of 95/100 places this address in the top tier of severity. Block and investigate any historical connections.
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.
Botnet C2 infrastructure has evolved from centralized IRC channels to resilient peer-to-peer networks, domain generation algorithms, and blockchain-based communication. This evolution makes botnet takedowns increasingly difficult and expensive.
Correlating logs across web servers, firewalls, DNS, and authentication systems reveals attack patterns invisible in individual log sources. Modern SIEM platforms use statistical analysis to connect related events across time and systems.