IP Threat Report
103.163.220.7
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 | |
| Burst 11/10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst 7/2s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 11 | Medium-risk: admin panels, config files | +60 | |
| Danger strong hits: 10 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| UA bot: Go-http-client | Known bot/crawler User-Agent detected | +40 |
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 2193 malicious IPs from this autonomous system.
Recommendations
Actions taken & recommended
- IP 103.163.220.7 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 103.163.220.0/24
- Report abuse to the network provider via their abuse contact
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
🔎 Path Enumeration Protection
Block scanning from 103.163.220.7: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
🌊 Traffic Flood Defense
IP 103.163.220.7 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 103.163.220.7: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
Neighbors in 103.163.220.0/24
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
103.163.220.7 has been assigned a threat score of 295/100 (Critical). This represents a critical risk level. Our detection systems have flagged multiple high-confidence indicators of malicious intent from this address.
The following attack categories were identified:
📊 Threat Analysis
IP address 103.163.220.7 has been traced to Tokyo, Japan, operating on the network of F.N.S. HOLDINGS LIMITED. Our threat detection systems have flagged this address based on observed malicious behavior patterns. The address has been active for 3 days in our monitoring system, producing 36 flagged requests at a rate of ~12/day. 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. With 3 different attack patterns detected, this IP exhibits behavior characteristic of advanced automated scanning frameworks. Japan currently accounts for 1,341 blocked IPs in our database, making it a major source of malicious traffic. A score of 295/100 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
Security Intelligence
💡 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.
💡 Digital Forensics Fundamentals
Digital forensics preserves and analyzes electronic evidence following attacks. Proper chain of custody, forensic imaging, timeline reconstruction, and artifact analysis are essential for understanding attack scope, attribution, and preventing recurrence.