
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.
We have detected 6570 malicious IPs from this autonomous system.
Add 104.234.32.121 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.
104.234.32.121 has been assigned a threat score of 90/100 (Critical). A score this high marks a critical threat actor. This address has demonstrated persistent, aggressive malicious behavior across multiple detection vectors.
Threat intelligence analysis has linked 104.234.32.121 to malicious activity originating from Chicago, United States, operating on the network of F.N.S. HOLDINGS LIMITED. The address has been under observation since its initial detection. During its 24-day observation window, we recorded 191 hostile requests from this IP — roughly 8 per day on average. With 36,307 flagged addresses, United States represents a major presence in our threat database. A score of 90/100 places this address in the top tier of severity. Block and investigate any historical connections.
Botnet C2 infrastructure has evolved from centralized IRC channels to resilient peer-to-peer networks, domain generation algorithms, and blockchain-based communication. This evolution makes botnet takedowns increasingly difficult and expensive.
GraphQL APIs introduce specific vulnerabilities including introspection information disclosure, query complexity attacks, batching abuse, and authorization bypass through nested queries. Depth limiting, cost analysis, and field-level authorization address these GraphQL-specific threats.