IP Threat Report
172.197.162.40
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 172.197.162.40 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 172.197.162.40 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
172.197.162.40 has been assigned a threat score of 85/100 (Critical). A score this high marks a critical threat actor. This address has demonstrated persistent, aggressive malicious behavior across multiple detection vectors.
📊 Threat Analysis
Threat intelligence analysis has linked 172.197.162.40 to malicious activity originating from Kuala Lumpur, MY, operating on the network of Foxtel ISP. The address has been under observation since its initial detection. The address has been active for 13 days in our monitoring system, producing 1,222 flagged requests at a rate of ~94/day. Our records show 101 malicious IPs originating from MY, positioning it as a significant contributor to global threat activity. A threat score of 85/100 places this IP in the high-risk category. Blocking at the firewall level is recommended.
Related Threats
Security Intelligence
💡 Threat Score Calculation Methods
Threat scoring combines multiple signals — request patterns, known signatures, IP reputation, geographic risk, and behavioral analysis — into a single actionable metric. Weighted scoring models allow tuning sensitivity to balance security with usability.
💡 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.