IP Threat Report
23.236.141.47
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| Directory Scan | 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 23.236.141.47 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
⚙️ Defensive Recommendations
Block 23.236.141.47 at the network perimeter. Implement defense-in-depth combining IP blocking with application-layer protections.
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
23.236.141.47 has been assigned a threat score of 95/100 (Critical). This is a critical-level threat. Systems administrators should treat this IP as hostile and block all inbound connections without exception.
📊 Threat Analysis
23.236.141.47 is registered in Buffalo, United States, operating on the network of B2 Net Solutions Inc.. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. Over a period of 7 days, this IP generated 601 malicious requests, averaging approximately 85.9 requests per day. Our records show 101 malicious IPs originating from United States, positioning it as a significant contributor to global threat activity. At 95/100, this is an extremely high-risk address. All traffic should be considered hostile.
Related Threats
🇺🇸 Top threats from United States
104.28.246.115 (350)103.215.74.213 (340)103.168.66.237 (340)34.187.158.4 (340)34.186.187.208 (340)View all →Security Intelligence
💡 Behavioral Analysis vs Signature Detection
Signature-based detection matches known attack patterns but misses novel threats. Behavioral analysis identifies anomalies in request patterns, timing, and volume, catching zero-day attacks that signatures cannot recognize.
💡 HTTP Header Analysis for Threat Detection
Examining HTTP headers beyond User-Agent reveals attack tools and automated scripts. Missing standard headers, unusual ordering, non-standard values, and inconsistencies with claimed client identity all serve as reliable detection signals.