
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.
Add 199.255.218.7 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.
199.255.218.7 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.
Threat intelligence analysis has linked 199.255.218.7 to malicious activity originating from Sydney, Canada, operating on the network of EastLink. The address has been under observation since its initial detection. The address has been active for 1 days in our monitoring system, producing 1 flagged requests at a rate of ~1/day. This is a residential IP address, suggesting a compromised home device such as a router, smart appliance, or infected workstation participating in a botnet. With 106 flagged addresses, Canada represents a significant presence in our threat database. With a threat score of 103/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly recommended.
This IP is classified as residential, suggesting it may belong to a compromised home device, IoT botnet member, or an infected personal computer. Residential IPs involved in attacks often indicate malware infection without the owner's knowledge.
Credential stuffing uses stolen username-password pairs from data breaches to attempt logins across many websites. Since users frequently reuse passwords, these automated attacks achieve success rates of 0.1-2%, which translates to thousands of compromised accounts from millions of attempts.
Advanced techniques enable threat detection while minimizing privacy impact. Encrypted DNS, differential privacy in analytics, and federated learning for threat models allow effective security monitoring without unnecessary surveillance of legitimate user behavior.