
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 31.152.48.36 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.
31.152.48.36 has been assigned a threat score of 60/100 (High). This score indicates high threat severity. The IP has shown clear patterns of malicious behavior that warrant immediate defensive measures.
Threat intelligence analysis has linked 31.152.48.36 to malicious activity originating from Thessaloniki, Greece, operating on the network of Cosmote Mobile Telecommunication S.A. The address has been under observation since its initial detection. During its 13-day observation window, we recorded 40 hostile requests from this IP — roughly 3.1 per day on average. Our records show 55 malicious IPs originating from Greece, positioning it as a notable contributor to global threat activity. The score of 60/100 warrants active monitoring and rate-limiting. Full blocking is advisable for sensitive systems.
Hacktivism combines hacking skills with political or social motivations. DDoS campaigns, website defacements, and data leaks target organizations based on ideological disagreements, adding unpredictable threat actors to the landscape.
Machine learning models analyze vast amounts of network traffic to identify attack patterns invisible to rule-based systems. Supervised models classify known attack types while unsupervised models detect anomalies that may indicate novel threats.