
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger medium hits: 5 | Medium-risk: admin panels, config files | +50 | |
| Danger medium hits: 4 | Medium-risk: admin panels, config files | +40 | |
| Danger medium hits: 6 | Medium-risk: admin panels, config files | +60 | |
| Danger medium hits: 8 | Medium-risk: admin panels, config files | +60 | |
| Danger medium hits: 10 | Medium-risk: admin panels, config files | +60 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Block 66.249.73.130 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.
66.249.73.130 has been assigned a threat score of 60/100 (High). This classifies it as a high-severity threat. Proactive blocking is recommended for sensitive infrastructure.
The address 66.249.73.130 originates from Mountain View, United States, operating on the network of Google LLC. It was identified through automated analysis of incoming network traffic across monitored endpoints. During its 3-day observation window, we recorded 15 hostile requests from this IP — roughly 5 per day on average. Operating from a residential network, this IP may represent a compromised home gateway or IoT device that has been drafted into a larger attack infrastructure. United States currently accounts for 202 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 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.
SQL injection remains one of the most common web attack vectors. Attackers inject malicious SQL code through input fields to extract database contents, modify data, or gain administrative access. Automated scanners test for SQLi vulnerabilities at massive scale.
The vast IPv6 address space makes traditional sequential scanning impractical. However, attackers use DNS records, certificate transparency logs, and predictable address patterns to identify active IPv6 hosts, adapting their techniques to the expanded address space.