
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger medium hits: 5 | Medium-risk: admin panels, config files | +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.
Add 113.204.79.230 to your firewall blocklist. Review logs for successful connections. Enable comprehensive logging on all public-facing services.
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.
113.204.79.230 has been assigned a threat score of 60/100 (High). At this threat level, the IP is considered high risk. Firewall rules should be updated to deny traffic from this source.
Threat intelligence analysis has linked 113.204.79.230 to malicious activity originating from Jinrongjie, China, operating on the network of CHINA UNICOM China169 Backbone. The address has been under observation since its initial detection. Over a period of 1 days, this IP generated 130 malicious requests, averaging approximately 130 requests per day. This IP is identified as a VPN or proxy endpoint, commonly used to mask the true origin of attack traffic and bypass geographic or reputation-based blocking. China currently accounts for 164 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 associated with a VPN or proxy service. Attackers frequently route their traffic through anonymizing services to obscure their true location. This makes attribution more challenging but the malicious behavior patterns remain detectable.
Prototype pollution manipulates JavaScript object prototypes to inject properties that affect all objects in an application. This can lead to denial of service, property injection, and in some cases remote code execution in Node.js applications.
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.