
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger medium hits: 5 | Medium-risk: admin panels, config files | +50 | |
| 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.
Block 18.192.211.45 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.
18.192.211.45 has been assigned a threat score of 60/100 (High). At this threat level, the IP is considered high risk. Firewall rules should be updated to deny traffic from this source.
Network traffic from 18.192.211.45, located in Frankfurt am Main, Germany, operating on the network of Amazon Technologies Inc., has been classified as malicious by our automated threat scoring engine. The address has been active for 1 days in our monitoring system, producing 1 flagged requests at a rate of ~1/day. This address belongs to a datacenter or cloud hosting provider. Hosting IPs are frequently leveraged by threat actors who rent cheap VPS instances specifically for conducting attacks. Germany currently accounts for 101 blocked IPs in our database, making it a significant source of malicious traffic. The score of 60/100 warrants active monitoring and rate-limiting. Full blocking is advisable for sensitive systems.
This IP belongs to a hosting or data center provider. Malicious traffic from hosting infrastructure often originates from compromised VPS instances, rented servers used for scanning campaigns, or abused free-tier cloud accounts. Hosting providers typically respond to abuse reports within 24-72 hours.
RCE vulnerabilities allow attackers to execute arbitrary code on target servers. These critical flaws often arise from deserialization bugs, template injection, or file upload vulnerabilities, and represent the highest severity class of web application weaknesses.
TLS fingerprinting creates unique identifiers based on how clients negotiate encrypted connections. The JA3 and JA4 methods generate hashes from TLS ClientHello parameters, enabling identification of specific tools and malware regardless of IP address changes.