
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.
Add 193.36.224.83 to your firewall blocklist. Review logs for successful connections. Enable comprehensive logging on all public-facing services.
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.
193.36.224.83 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 address 193.36.224.83 originates from Miami, United States, operating on the network of F.N.S. HOLDINGS LIMITED. It was identified through automated analysis of incoming network traffic across monitored endpoints. Our sensors captured 146 malicious requests from this address across a 2-day span, reflecting a sustained attack cadence of ~73 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. United States currently accounts for 152 blocked IPs in our database, making it a significant source of malicious traffic. At 100/100, 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.
Analyzing User-Agent strings reveals automated tools masquerading as legitimate browsers. Inconsistencies between claimed browser capabilities and actual behavior, impossible version combinations, and known scanner signatures help identify malicious clients.
False positives erode trust in security systems and waste analyst resources. Effective management requires feedback loops, allowlisting mechanisms, contextual analysis, and regular tuning of detection rules based on operational experience.