39.105.202.192 Threat Intelligence and Host Information
Feb 27, 2026
ipinfopage
General
IP Address
39.105.202.192
Location
🇨🇳 Beijing, China
Network
AS37963
Threat Score
50/100
Attack Intelligence
MITRE ATT&CK Techniques
T1190 - Exploit Public-Facing Application, T1498 - Network Denial of Service
Open Ports Detected
3306
Geographic Location
Country
China
City
Beijing
Region
Beijing
Coordinates
39.9075, 116.3972
Network Information
ASN
AS37963
Organization
Hangzhou Alibaba Advertising Co.,Ltd.
Network
AS37963 Hangzhou Alibaba Advertising Co.,Ltd.
WHOIS Information
inetnum
39.96.0.0 - 39.108.255.255
netname
ALISOFT
descr
Alibaba (US) Technology Co., Ltd.
country
CN
admin-c
IP50-AP
tech-c
IP50-AP
abuse-c
AC1601-AP
status
ALLOCATED PORTABLE
mnt-by
MAINT-CNNIC-AP
mnt-irt
IRT-CNNIC-CN
last-modified
2019-08-07T23:28:05Z
irt
IRT-CNNIC-CN
address
Zhejiang, China, 310099
e-mail
abuse@alibaba-inc.com
abuse-mailbox
ipas@cnnic.cn
role
ABUSE CNNICCN
phone
+86-0571-85022088-30763
nic-hdl
ZM877-AP
person
Guowei Pan
fax-no
+86-0571-85022600
route
39.104.0.0/14
origin
AS45102
Attack Logs
| Date | Target Location | Protocol | Link |
|---|---|---|---|
| 2026-02-22 | Digitaloceantoronto-Redis | MULTIPLE | View Log |
- Country: China
- Network:
- Noticed: 50 times
- Protocols Attacked: portscan redis
- Countries Attacked: Australia, Finland, France, Germany, Poland, United States of America
CVEs Detected
CVE-2019-7317 CVE-2020-14814 CVE-2020-14830 CVE-2020-14837 CVE-2020-14839 CVE-2020-14845 CVE-2020-14846 CVE-2020-14852 CVE-2020-15358 CVE-2020-1971 CVE-2021-22570 CVE-2023-21977 CVE-2023-22028 CVE-2023-22084
Disclaimer
This page contains threat intelligence information for the IPv4 address 39.105.202.192 and was generated either as a result of observed malicious activity or as an information gathering exercise to assist with enrichment of security events and context. All information is gathered passively through aggregation of public sources, or observations through activity upon honeynets. The host score is calculated through a series of statistically weighted values and machine learning which takes into account metadata such as host information, frequency, volume and global distribution of malicious activity, association with other known malicious hosts or networks, proxying or anonymising behaviour such as with tor exit nodes, residential proxies or VPN services, and many other attributes. These values are historical and indicative only - and should not be taken to be an accurate representation of the users, businesses or networks in which they reside.