IP Threat Report
1.39.158.205
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 1.39.158.205 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 1.39.158.205 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
1.39.158.205 has been assigned a threat score of 70/100 (High). At this threat level, the IP is considered high risk. Firewall rules should be updated to deny traffic from this source.
📊 Threat Analysis
Threat intelligence analysis has linked 1.39.158.205 to malicious activity originating from Sīkar, India, operating on the network of Vodafone Essar Limited. The address has been under observation since its initial detection. Our sensors captured 74 malicious requests from this address across a 26-day span, reflecting a sustained attack cadence of ~2.8 requests per day. India currently accounts for 101 blocked IPs in our database, making it a significant source of malicious traffic. The score of 70/100 indicates a confirmed malicious actor. Network-level blocking is appropriate.
Related Threats
Security Intelligence
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💡 Insider Threat Indicators
Insider threats — whether malicious or negligent — account for a significant percentage of data breaches. Behavioral analytics detecting unusual access patterns, data downloads, and privilege escalation help identify insider risks before damage occurs.