
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger strong hits: 3 | High-risk paths: shells, RCE vectors, exploits | +75 | |
| Danger medium hits: 2 | Medium-risk: admin panels, config files | +20 | |
| POST requests present | Behavioral anomaly detected by automated analysis | +8 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Block 41.220.200.134 at the network perimeter. Implement defense-in-depth combining IP blocking with application-layer protections.
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.
41.220.200.134 has been assigned a threat score of 103/100 (Critical). This represents a critical risk level. Our detection systems have flagged multiple high-confidence indicators of malicious intent from this address.
Our monitoring infrastructure has identified 41.220.200.134, geolocated to Maputo, MZ, operating on the network of TMCEL - Moçambique Telecom, SA, as a source of suspicious network activity. Over a period of 1 days, this IP generated 1 malicious requests, averaging approximately 1 requests per day. Classified as a VPN or proxy server, this IP serves as an anonymization layer. While VPNs have legitimate uses, this address has been observed routing clearly malicious traffic. MZ currently accounts for 22 blocked IPs in our database, making it a notable source of malicious traffic. At 103/100, this is an extremely high-risk address. All traffic should be considered hostile.
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.
SQL injection remains one of the most common web attack vectors. Attackers inject malicious SQL code through input fields to extract database contents, modify data, or gain administrative access. Automated scanners test for SQLi vulnerabilities at massive scale.
Effective rate limiting must balance protection against abuse with allowing legitimate traffic bursts. Sliding window algorithms, token buckets, and adaptive thresholds based on client reputation provide layered defense against flooding attacks.