
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger medium hits: 3 | Medium-risk: admin panels, config files | +30 | |
| Danger strong hits: 4 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| 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 103.112.14.34 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.
103.112.14.34 has been assigned a threat score of 140/100 (Critical). This places it in the critical threat category. Immediate blocking is strongly advised across all network perimeters.
103.112.14.34 is registered in Kanpur, India, operating on the network of Jai Mata Di Telectronix Private Limited. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. Over a period of 4 days, this IP generated 143 malicious requests, averaging approximately 35.8 requests per day. This residential IP is likely a compromised consumer device. Home routers and IoT equipment with default credentials are prime targets for botnet operators. Our records show 4,286 malicious IPs originating from India, positioning it as a major contributor to global threat activity. A score of 140/100 places this address in the top tier of severity. Block and investigate any historical connections.
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.
Request smuggling exploits differences in how front-end and back-end servers parse HTTP requests. This technique can bypass security controls, poison web caches, and hijack other users sessions by desynchronizing request boundaries.
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.