IP Threat Report
34.162.126.222
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| Burst 14/2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 45/10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 11 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 14 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 22 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 45 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 52 | Medium-risk: admin panels, config files | +60 | |
| Danger medium hits: 64 | Medium-risk: admin panels, config files | +60 | |
| Danger strong hits: 17 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger strong hits: 431 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger strong hits: 448 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| POST requests present | Behavioral anomaly detected by automated analysis | +8 | |
| POST seen | Behavioral anomaly detected by automated analysis | +8 |
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
Network Provider
Recommendations
Actions taken & recommended
- IP 34.162.126.222 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 34.162.126.0/24
- Report abuse to the network provider via their abuse contact
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
🌊 Flood / DDoS Mitigation
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 34.162.126.222.
Neighbors in 34.162.126.0/24
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
34.162.126.222 has been assigned a threat score of 238/100 (Critical). With this rating, the IP falls into the critical severity bracket — among the most dangerous addresses in our monitoring database.
The following attack categories were identified:
📊 Threat Analysis
IP address 34.162.126.222 has been traced to Columbus, United States, operating on the network of Google LLC. Our threat detection systems have flagged this address based on observed malicious behavior patterns. Our sensors captured 508 malicious requests from this address across a 6-day span, reflecting a sustained attack cadence of ~84.7 requests per day. Classified as a hosting IP, this address likely runs on a rented server or cloud instance. Attackers prefer datacenter IPs for their high bandwidth and disposable nature. Rate-based attacks from this IP aim to overwhelm server resources through high-volume request flooding. With 141 flagged addresses, United States represents a significant presence in our threat database. A score of 238/100 places this address in the top tier of severity. Block and investigate any historical connections.
This IP belongs to a hosting or data center provider. Malicious traffic from hosting infrastructure often originates from compromised VPS instances, rented servers used for scanning campaigns, or abused free-tier cloud accounts. Hosting providers typically respond to abuse reports within 24-72 hours.
Related Threats
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💡 DDoS Mitigation Approaches
Distributed denial of service attacks overwhelm infrastructure with traffic volume. Effective mitigation combines always-on traffic scrubbing, anycast network distribution, rate limiting, and the ability to quickly scale absorption capacity during attacks.
💡 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.