IP Threat Report
51.222.25.73
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| DDoS / Flood | Behavioral anomaly detected by automated analysis | +0 |
Observed Activity
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Timeline
Recommendations
Actions taken & recommended
- IP 51.222.25.73 is blocked at application level (HTTP 403)
- Consider blocking at firewall level (iptables/CSF) to reduce server load
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
⚙️ General Security
Add 51.222.25.73 to your firewall blocklist. Review logs for successful connections. Enable comprehensive logging on all public-facing services.
Blacklist Status (DNSBL)
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.
Threat Analysis
51.222.25.73 has been assigned a threat score of 70/100 (High). This classifies it as a high-severity threat. Proactive blocking is recommended for sensitive infrastructure.
📊 Threat Analysis
51.222.25.73 is registered in Beauharnois, Canada, operating on the network of OVH SAS. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. Our sensors captured 52 malicious requests from this address across a 120-day span, reflecting a sustained attack cadence of ~0.4 requests per day. With 101 flagged addresses, Canada represents a significant presence in our threat database. A threat score of 70/100 places this IP in the high-risk category. Blocking at the firewall level is recommended.
Related Threats
Security Intelligence
💡 DDoS Mitigation Approaches
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.
💡 Privacy-Preserving Threat Detection
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.