IP Threat Report
35.252.27.234
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 35.252.27.234 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 35.252.27.234 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
35.252.27.234 has been assigned a threat score of 130/100 (Critical). This is a critical-level threat. Systems administrators should treat this IP as hostile and block all inbound connections without exception.
📊 Threat Analysis
Threat intelligence analysis has linked 35.252.27.234 to malicious activity originating from Tel Aviv, IL, operating on the network of Google LLC. The address has been under observation since its initial detection. Over a period of 4 days, this IP generated 613 malicious requests, averaging approximately 153.3 requests per day. IL currently accounts for 102 blocked IPs in our database, making it a significant source of malicious traffic. With a threat score of 130/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly recommended.
Related Threats
Security Intelligence
💡 Rate Limiting and Throttling Strategies
Effective rate limiting must balance protection against abuse with allowing legitimate traffic bursts. Sliding window algorithms, token buckets, and adaptive thresholds based on client reputation provide layered defense against flooding attacks.
💡 Autonomous System Analysis
Analyzing attack patterns at the AS (Autonomous System) level reveals which networks harbor the most malicious activity. Some ASes have abuse rates orders of magnitude higher than average, indicating lax enforcement of acceptable use policies.