IP Threat Report
34.162.49.127
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| Burst 19/2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 21/10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 19 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 21 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 6 | Medium-risk: admin panels, config files | +60 | |
| Foreign referer | Referer from unrelated external domain | +10 | |
| Foreign referer seen | Referer from unrelated external domain | +10 | |
| UA changed | Multiple User-Agents — bot rotation technique | +25 | |
| UA changed for same IP | Multiple User-Agents — bot rotation technique | +25 |
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 34.162.49.127 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 34.162.49.0/24
- 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 34.162.49.127.
🤖 User-Agent Anomaly Defense
IP 34.162.49.127 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
Neighbors in 34.162.49.0/24
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
34.162.49.127 has been assigned a threat score of 165/100 (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 34.162.49.127 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. Over a period of 6 days, this IP generated 482 malicious requests, averaging approximately 80.3 requests per day. This address belongs to a datacenter or cloud hosting provider. Hosting IPs are frequently leveraged by threat actors who rent cheap VPS instances specifically for conducting attacks. The dual attack vectors of Request Flooding combined with User-Agent Anomaly indicate a coordinated assault rather than opportunistic scanning. Our records show 143 malicious IPs originating from United States, positioning it as a significant contributor to global threat activity. At 165/100, this is an extremely high-risk address. All traffic should be considered hostile.
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.
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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.
💡 Open Redirect Exploitation
Open redirect vulnerabilities allow attackers to redirect users from trusted domains to malicious sites. While often underestimated, these flaws enable convincing phishing, token theft through redirect-based OAuth flows, and SSRF chains.