
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Directory Scan | Behavioral anomaly detected by automated analysis | +0 | |
| DDoS / Flood | 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 148.66.155.73 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.
148.66.155.73 has been assigned a threat score of 200/100 (Critical). This is a critical-level threat. Systems administrators should treat this IP as hostile and block all inbound connections without exception.
The address 148.66.155.73 originates from Singapore, Singapore, operating on the network of GoDaddy.com, LLC. It was identified through automated analysis of incoming network traffic across monitored endpoints. The address has been active for 12 days in our monitoring system, producing 323 flagged requests at a rate of ~26.9/day. Our records show 102 malicious IPs originating from Singapore, positioning it as a significant contributor to global threat activity. With a threat score of 200/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly recommended.
Distributed denial of service attacks overwhelm infrastructure with traffic volume. Effective mitigation combines always-on traffic scrubbing, anycast network distribution, rate limiting, and the ability to quickly scale absorption capacity during attacks.
BEC attacks use compromised or spoofed executive email accounts to request fraudulent wire transfers or sensitive data. These attacks cause billions in annual losses and rely on social engineering rather than technical exploitation.