IP Threat Report
20.168.65.162
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: 18 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 377 | Medium-risk: admin panels, config files | +60 | |
| Burst: 17 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 55 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger medium hits: 252 | Medium-risk: admin panels, config files | +60 | |
| Burst: 15 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 50 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 24 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 378 | Medium-risk: admin panels, config files | +60 | |
| Burst: 61 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 18 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 62 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 64 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 20.168.65.162 is blocked at application level (HTTP 403)
- Consider blocking at firewall level (iptables/CSF) to reduce server load
- Report abuse to the network provider via their abuse contact
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
🤖 User-Agent Anomaly Defense
IP 20.168.65.162 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
🌊 Traffic Flood Defense
IP 20.168.65.162 is generating excessive traffic. Limit connections per source IP. Enable geographic blocking if traffic from this region is unexpected.
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
20.168.65.162 has been assigned a threat score of 245/100 (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
The address 20.168.65.162 originates from Phoenix, United States, operating on the network of Microsoft Corporation. It was identified through automated analysis of incoming network traffic across monitored endpoints. Over a period of 1 days, this IP generated 5 malicious requests, averaging approximately 5 requests per day. 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 101 malicious IPs originating from United States, positioning it as a significant contributor to global threat activity. At 245/100, this is an extremely high-risk address. All traffic should be considered hostile.
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.
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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.
💡 IoT Device Compromise Patterns
Internet of Things devices are prime targets for botnet recruitment due to weak default credentials, infrequent updates, and always-on connectivity. Compromised IoT devices generate persistent scanning and attack traffic without their owners knowledge.