
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| Foreign referer | 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 scanning from 66.231.79.53: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
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.
66.231.79.53 has been assigned a threat score of 75/100 (High). This classifies it as a high-severity threat. Proactive blocking is recommended for sensitive infrastructure.
The following attack categories were identified:
Threat intelligence analysis has linked 66.231.79.53 to malicious activity originating from Guayaquil, EC, operating on the network of Servitractor S.A.. The address has been under observation since its initial detection. The address has been active for 5 days in our monitoring system, producing 107 flagged requests at a rate of ~21.4/day. 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. Active path scanning has been detected — this IP probes for hundreds of common file and directory names. Our records show 80 malicious IPs originating from EC, positioning it as a notable contributor to global threat activity. The score of 75/100 indicates a confirmed malicious actor. Network-level blocking is appropriate.
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.
Vulnerability scanning is the automated process of probing web applications for known weaknesses. Attackers use tools like Nuclei, Nikto, and ZAP to test thousands of hosts per hour, looking for exposed configuration files, outdated software, and default credentials.
Signature-based detection matches known attack patterns but misses novel threats. Behavioral analysis identifies anomalies in request patterns, timing, and volume, catching zero-day attacks that signatures cannot recognize.