IP Threat Report
222.176.200.7
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA changed for same IP | Multiple User-Agents — bot rotation technique | +25 | |
| Burst: 5 req / 2s | Abnormally fast request rate — automated scanning | +35 |
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 222.176.200.7 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 222.176.200.0/24
- Report abuse to the network provider via their abuse contact
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
🤖 Bot Detection
Address UA spoofing from 222.176.200.7: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
🌊 Flood / DDoS Mitigation
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 222.176.200.7.
Neighbors in 222.176.200.0/24
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
222.176.200.7 has been assigned a threat score of 60/100 (High). At this threat level, the IP is considered high risk. Firewall rules should be updated to deny traffic from this source.
The following attack categories were identified:
📊 Threat Analysis
The address 222.176.200.7 originates from Chongqing, China, operating on the network of Chinanet. It was identified through automated analysis of incoming network traffic across monitored endpoints. Over a period of 1 days, this IP generated 1 malicious requests, averaging approximately 1 requests per day. The address is classified as residential, meaning it likely belongs to an end-user ISP connection. Malicious activity from residential IPs typically indicates device compromise or botnet membership. The dual attack vectors of User-Agent Anomaly combined with Request Flooding indicate a coordinated assault rather than opportunistic scanning. China currently accounts for 202 blocked IPs in our database, making it a significant source of malicious traffic. At 60/100, this IP presents a meaningful threat. Implement rate limiting with escalation to blocking.
This IP is classified as residential, suggesting it may belong to a compromised home device, IoT botnet member, or an infected personal computer. Residential IPs involved in attacks often indicate malware infection without the owner's knowledge.
Related Threats
Security Intelligence
💡 User-Agent Analysis Techniques
Analyzing User-Agent strings reveals automated tools masquerading as legitimate browsers. Inconsistencies between claimed browser capabilities and actual behavior, impossible version combinations, and known scanner signatures help identify malicious clients.
💡 GraphQL Security Risks
GraphQL APIs introduce specific vulnerabilities including introspection information disclosure, query complexity attacks, batching abuse, and authorization bypass through nested queries. Depth limiting, cost analysis, and field-level authorization address these GraphQL-specific threats.