IP Threat Report
172.213.8.171
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA suspicious (short/empty) | Behavioral anomaly detected by automated analysis | +15 | |
| Danger strong hits: 3 | High-risk paths: shells, RCE vectors, exploits | +75 | |
| Danger medium hits: 201 | Medium-risk: admin panels, config files | +60 | |
| Burst: 59 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 198 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 134 | Medium-risk: admin panels, config files | +60 | |
| Burst: 56 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 194 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 4 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Burst: 49 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 163 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 42 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 132 req / 10s | 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 172.213.8.171 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 172.213.8.0/24
- 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 172.213.8.171: 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 172.213.8.171.
Neighbors in 172.213.8.0/24
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
172.213.8.171 has been assigned a threat score of 245/100 (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
Network traffic from 172.213.8.171, located in Milan, Italy, operating on the network of Microsoft Corporation, has been classified as malicious by our automated threat scoring engine. During its 1-day observation window, we recorded 4 hostile requests from this IP — roughly 4 per day on average. This address belongs to a datacenter or cloud hosting provider. Hosting IPs are frequently leveraged by threat actors who rent cheap VPS instances specifically for conducting attacks. The dual attack vectors of User-Agent Anomaly combined with Request Flooding indicate a coordinated assault rather than opportunistic scanning. Our records show 102 malicious IPs originating from Italy, positioning it as a significant contributor to global threat activity. With a threat score of 245/100, 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
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.
💡 Content Delivery Network Risks
CDNs can inadvertently mask the true origin of malicious traffic, making attribution difficult. Attackers abuse CDN services to proxy their attacks, leverage cached content for amplification, and exploit misconfigurations in CDN-to-origin connections.