IP Threat Report
85.203.23.47
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger strong hits: 184 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 284 | Medium-risk: admin panels, config files | +60 | |
| Burst: 5 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 14 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Foreign referer seen | Referer from unrelated external domain | +10 | |
| UA bot: Go-http-client | Known bot/crawler User-Agent detected | +40 | |
| Danger strong hits: 1 | High-risk paths: shells, RCE vectors, exploits | +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 85.203.23.47 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 85.203.23.0/24
- 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 85.203.23.47.
🤖 Bot Detection
Address UA spoofing from 85.203.23.47: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
Neighbors in 85.203.23.0/24
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
85.203.23.47 has been assigned a threat score of 240/100 (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
Network traffic from 85.203.23.47, located in Singapore, Singapore, operating on the network of GSL Networks Pty LTD, has been classified as malicious by our automated threat scoring engine. The address has been active for 37 days in our monitoring system, producing 2 flagged requests at a rate of ~0.1/day. Classified as a VPN or proxy server, this IP serves as an anonymization layer. While VPNs have legitimate uses, this address has been observed routing clearly malicious traffic. The dual attack vectors of Request Flooding combined with User-Agent Anomaly indicate a coordinated assault rather than opportunistic scanning. Our records show 135 malicious IPs originating from Singapore, positioning it as a significant contributor to global threat activity. A score of 240/100 places this address in the top tier of severity. Block and investigate any historical connections.
This IP is associated with a VPN or proxy service. Attackers frequently route their traffic through anonymizing services to obscure their true location. This makes attribution more challenging but the malicious behavior patterns remain detectable.
Related Threats
🇸🇬 Top threats from Singapore
85.203.23.12 (340)85.203.23.31 (330)84.17.39.195 (325)192.166.246.30 (325)85.203.21.101 (320)View all →Security Intelligence
💡 Brute Force Attack Mechanics
Brute force attacks systematically try username and password combinations to gain unauthorized access. Modern attacks leverage credential databases from previous breaches, testing millions of combinations using distributed botnets across multiple IP addresses.
💡 Threat Score Calculation Methods
Threat scoring combines multiple signals — request patterns, known signatures, IP reputation, geographic risk, and behavioral analysis — into a single actionable metric. Weighted scoring models allow tuning sensitivity to balance security with usability.