
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger medium hits: 1 | Medium-risk: admin panels, config files | +10 | |
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| Directory Scan | Behavioral anomaly detected by automated analysis | +0 | |
| UA changed | Multiple User-Agents — bot rotation technique | +25 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
IP 188.213.202.104 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
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.
188.213.202.104 has been assigned a threat score of 100/100 (Critical). This is a critical-level threat. Systems administrators should treat this IP as hostile and block all inbound connections without exception.
The following attack categories were identified:
Threat intelligence analysis has linked 188.213.202.104 to malicious activity originating from Tampa, United States, operating on the network of GSL Networks Pty LTD. The address has been under observation since its initial detection. During its 38-day observation window, we recorded 1,223 hostile requests from this IP — roughly 32.2 per day on average. Detected suspicious User-Agent anomalies including empty, forged, or rapidly rotating UA strings — characteristic of automated scanning tools. With 151 flagged addresses, United States represents a significant presence in our threat database. A score of 100/100 places this address in the top tier of severity. Block and investigate any historical connections.
XXE vulnerabilities in XML parsers allow attackers to read local files, perform SSRF, and execute denial of service attacks. Many legacy applications and APIs remain vulnerable to XXE due to insecure default XML parser configurations.
Advanced techniques enable threat detection while minimizing privacy impact. Encrypted DNS, differential privacy in analytics, and federated learning for threat models allow effective security monitoring without unnecessary surveillance of legitimate user behavior.