IP Threat Report
162.158.111.142
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 162.158.111.142 is blocked at application level (HTTP 403)
- Consider blocking at firewall level (iptables/CSF) to reduce server load
- Other malicious IPs detected in the same /24 subnet — consider blocking 162.158.111.0/24
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
⚙️ Defensive Recommendations
Block 162.158.111.142 at the network perimeter. Implement defense-in-depth combining IP blocking with application-layer protections.
Neighbors in 162.158.111.0/24
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
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
162.158.111.142 has been assigned a threat score of 65/100 (High). This classifies it as a high-severity threat. Proactive blocking is recommended for sensitive infrastructure.
📊 Threat Analysis
Our monitoring infrastructure has identified 162.158.111.142, geolocated to Frankfurt, Germany, operating on the network of Cloudflare, Inc., as a source of suspicious network activity. Over a period of 32 days, this IP generated 409 malicious requests, averaging approximately 12.8 requests per day. Our records show 121 malicious IPs originating from Germany, positioning it as a significant contributor to global threat activity. The score of 65/100 warrants active monitoring and rate-limiting. Full blocking is advisable for sensitive systems.
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💡 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.
💡 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.