IP Threat Report
173.239.211.150
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 | |
| Danger strong hits: 57 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 1 | Medium-risk: admin panels, config files | +10 | |
| Burst: 15 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 52 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| UA suspicious (short/empty) | Behavioral anomaly detected by automated analysis | +15 | |
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Danger strong hits: 1 | High-risk paths: shells, RCE vectors, exploits | +25 | |
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +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 173.239.211.150 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 173.239.211.0/24
- 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 173.239.211.150: 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 173.239.211.150.
🔎 Path Enumeration Protection
Block scanning from 173.239.211.150: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
Neighbors in 173.239.211.0/24
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
173.239.211.150 has been assigned a threat score of 205/100 (Critical). With this rating, the IP falls into the critical severity bracket — among the most dangerous addresses in our monitoring database.
The following attack categories were identified:
📊 Threat Analysis
IP address 173.239.211.150 has been traced to New York, United States, operating on the network of F.N.S. HOLDINGS LIMITED. Our threat detection systems have flagged this address based on observed malicious behavior patterns. Our sensors captured 9 malicious requests from this address across a 9-day span, reflecting a sustained attack cadence of ~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 diversity of 3 separate attack methods suggests a comprehensive attack toolkit — likely an automated scanner that tests for vulnerabilities across multiple categories. Our records show 140 malicious IPs originating from United States, positioning it as a significant contributor to global threat activity. At 205/100, this is an extremely high-risk address. All traffic should be considered hostile.
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.
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💡 TLS Fingerprinting (JA3/JA4)
TLS fingerprinting creates unique identifiers based on how clients negotiate encrypted connections. The JA3 and JA4 methods generate hashes from TLS ClientHello parameters, enabling identification of specific tools and malware regardless of IP address changes.
💡 Container Security Challenges
Containerized applications face unique security challenges including vulnerable base images, excessive privileges, shared kernel attacks, and insecure orchestration configurations. Runtime security monitoring and immutable container policies mitigate these risks.