IP Threat Report
38.38.253.211
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA bot: crawler | Known bot/crawler User-Agent detected | +40 | |
| Danger medium hits: 1 | Medium-risk: admin panels, config files | +10 |
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 38.38.253.211 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 38.38.253.211 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
Open Ports & Services
Network reconnaissance data from Shodan. Open ports may indicate running services, misconfigurations, or potential attack surfaces.
| Port | Service | Risk | Description |
|---|---|---|---|
| 22 | SSH | Low | Secure Shell — common brute force target for remote access |
| 2000 | Unknown | Low | Service on port 2000 |
| 2332 | Unknown | Low | Service on port 2332 |
| 5555 | Unknown | Low | Service on port 5555 |
| 6666 | Unknown | Low | Service on port 6666 |
| 6667 | Unknown | Low | Service on port 6667 |
| 7777 | Unknown | Low | Service on port 7777 |
| 7778 | Unknown | Low | Service on port 7778 |
| 8886 | Unknown | Low | Service on port 8886 |
| 8887 | Unknown | Low | Service on port 8887 |
| 8888 | HTTP-Alt | Low | Service on port 8888 |
| 8889 | Unknown | Low | Service on port 8889 |
| 8899 | Unknown | Low | Service on port 8899 |
| 9100 | Unknown | Low | Service on port 9100 |
| 10050 | Unknown | Low | Service on port 10050 |
Data source: Shodan InternetDB. Scanned independently of abuse.mom.
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
38.38.253.211 has been assigned a threat score of 50/100 (Medium). This is a moderate threat. While not the most dangerous, this IP shows patterns that warrant monitoring and potential rate-limiting.
The following attack categories were identified:
📊 Threat Analysis
Threat intelligence analysis has linked 38.38.253.211 to malicious activity originating from San Jose, United States, operating on the network of ZENLAYER.INC. The address has been under observation since its initial detection. During its 1-day observation window, we recorded 1 hostile requests from this IP — roughly 1 per day on average. Operating from a residential network, this IP may represent a compromised home gateway or IoT device that has been drafted into a larger attack infrastructure. Detected suspicious User-Agent anomalies including empty, forged, or rapidly rotating UA strings — characteristic of automated scanning tools. United States currently accounts for 161 blocked IPs in our database, making it a significant source of malicious traffic. The score of 50/100 warrants active monitoring and rate-limiting. Full blocking is advisable for sensitive systems.
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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💡 HTTP Header Analysis for Threat Detection
Examining HTTP headers beyond User-Agent reveals attack tools and automated scripts. Missing standard headers, unusual ordering, non-standard values, and inconsistencies with claimed client identity all serve as reliable detection signals.
💡 Web Application Firewall Strategies
WAFs inspect HTTP traffic to block common attacks but require careful tuning. Overly aggressive rules cause false positives while permissive configurations miss attacks. Modern WAFs combine signature matching with behavioral analysis and machine learning.