IP Threat Report
8.216.127.75
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 | |
| Burst: 10 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Foreign referer seen | Referer from unrelated external domain | +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 8.216.127.75 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
🤖 Bot Detection
Address UA spoofing from 8.216.127.75: 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 8.216.127.75.
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 |
| 111 | Unknown | Low | Service on port 111 |
| CVE ID | Link |
|---|---|
| CVE-2020-14145 | NVD → |
| CVE-2023-51767 | NVD → |
| CVE-2025-26465 | NVD → |
| CVE-2023-51385 | NVD → |
| CVE-2023-38408 | NVD → |
| CVE-2008-3844 | NVD → |
| CVE-2007-2768 | NVD → |
| CVE-2016-20012 | NVD → |
| CVE-2018-15473 | NVD → |
| CVE-2018-20685 | NVD → |
| CVE-2023-48795 | NVD → |
| CVE-2025-32728 | NVD → |
| CVE-2021-41617 | NVD → |
| CVE-2020-15778 | NVD → |
| CVE-2019-6109 | NVD → |
| CVE-2018-15919 | NVD → |
| CVE-2021-36368 | NVD → |
| CVE-2019-6111 | NVD → |
| CVE-2017-15906 | NVD → |
| CVE-2019-6110 | NVD → |
🔴 Security scanning identified 20 vulnerability entries on this host. This volume strongly suggests severely outdated software. Consult NVD advisories for details.
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
8.216.127.75 has been assigned a threat score of 105/100 (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
Our monitoring infrastructure has identified 8.216.127.75, geolocated to Tokyo, Japan, operating on the network of Alibaba (US) Technology Co., Ltd., as a source of suspicious network activity. Over a period of 1 days, this IP generated 1 malicious requests, averaging approximately 1 requests per day. 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. Two attack patterns were identified (User-Agent Anomaly and Request Flooding), suggesting a semi-automated campaign that targets multiple vulnerabilities. With 101 flagged addresses, Japan represents a significant presence in our threat database. With a threat score of 105/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly recommended.
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.
💡 DDoS Mitigation Approaches
Distributed denial of service attacks overwhelm infrastructure with traffic volume. Effective mitigation combines always-on traffic scrubbing, anycast network distribution, rate limiting, and the ability to quickly scale absorption capacity during attacks.