
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Malicious Activity | 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 162.158.110.123 at the network perimeter. Implement defense-in-depth combining IP blocking with application-layer protections.
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.
162.158.110.123 has been assigned a threat score of 65/100 (High). At this threat level, the IP is considered high risk. Firewall rules should be updated to deny traffic from this source.
162.158.110.123 is registered in Frankfurt, Germany, operating on the network of Cloudflare, Inc.. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. Our sensors captured 174 malicious requests from this address across a 2-day span, reflecting a sustained attack cadence of ~87 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. At 65/100, this IP presents a meaningful threat. Implement rate limiting with escalation to blocking.
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.
Buffer overflow vulnerabilities remain relevant in C/C++ applications despite decades of mitigation efforts. Modern protections like ASLR, stack canaries, and DEP reduce exploitability but determined attackers continue finding bypass techniques.
Analyzing attack patterns at the AS (Autonomous System) level reveals which networks harbor the most malicious activity. Some ASes have abuse rates orders of magnitude higher than average, indicating lax enforcement of acceptable use policies.