IP Threat Report
8.234.55.7
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| Burst 18/2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 23/2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 63/10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 82/10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 40 | Medium-risk: admin panels, config files | +60 | |
| Danger medium hits: 80 | Medium-risk: admin panels, config files | +60 | |
| Danger strong hits: 241 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger strong hits: 482 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| POST seen | Behavioral anomaly detected by automated analysis | +8 | |
| UA changed | 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 8.234.55.7 is blocked at application level (HTTP 403)
- Consider blocking at firewall level (iptables/CSF) to reduce server load
- Report abuse to the network provider via their abuse contact
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
🌊 Traffic Flood Defense
IP 8.234.55.7 is generating excessive traffic. Limit connections per source IP. Enable geographic blocking if traffic from this region is unexpected.
🤖 Bot Detection
Address UA spoofing from 8.234.55.7: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
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
8.234.55.7 has been assigned a threat score of 263/100 (Critical). This is a critical-level threat. Systems administrators should treat this IP as hostile and block all inbound connections without exception.
The following attack categories were identified:
📊 Threat Analysis
IP address 8.234.55.7 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. During its 5-day observation window, we recorded 212 hostile requests from this IP — roughly 42.4 per day on average. 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. The dual attack vectors of Request Flooding combined with User-Agent Anomaly indicate a coordinated assault rather than opportunistic scanning. United States currently accounts for 128 blocked IPs in our database, making it a significant source of malicious traffic. With a threat score of 263/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly recommended.
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.
💡 Web Application Firewall Strategies
WAFs inspect HTTP traffic to block common attacks but require careful tuning. Overly aggressive rules cause false positives while permissive configurations miss attacks. Modern WAFs combine signature matching with behavioral analysis and machine learning.