IP Threat Report
8.230.112.11
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| Burst 20/2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 72/10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 73/10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 40 | Medium-risk: admin panels, config files | +60 | |
| Danger strong hits: 241 | 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
We have detected 8213 malicious IPs from this autonomous system.
Recommendations
Actions taken & recommended
- IP 8.230.112.11 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 8.230.112.0/24
- 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 8.230.112.11.
🤖 User-Agent Anomaly Defense
IP 8.230.112.11 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
Neighbors in 8.230.112.0/24
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
8.230.112.11 has been assigned a threat score of 263/100 (Critical). A score this high marks a critical threat actor. This address has demonstrated persistent, aggressive malicious behavior across multiple detection vectors.
The following attack categories were identified:
📊 Threat Analysis
Threat intelligence analysis has linked 8.230.112.11 to malicious activity originating from Dallas, United States, operating on the network of Google LLC. The address has been under observation since its initial detection. During its 5-day observation window, we recorded 231 hostile requests from this IP — roughly 46.2 per day on average. The IP is classified as hosting/datacenter infrastructure, commonly associated with rented servers used for automated attack campaigns, botnet command-and-control, or vulnerability scanning at scale. Two attack patterns were identified (Request Flooding and User-Agent Anomaly), suggesting a semi-automated campaign that targets multiple vulnerabilities. Our records show 36,218 malicious IPs originating from United States, positioning it as a major contributor to global threat activity. 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.
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.
💡 False Positive Management
False positives erode trust in security systems and waste analyst resources. Effective management requires feedback loops, allowlisting mechanisms, contextual analysis, and regular tuning of detection rules based on operational experience.