1.14.190.102 Threat Intelligence and Host Information
Jun 14, 2024
ipinfopage
General
IP Address
1.14.190.102
Location
🇨🇳 China
Network
AS45090
Threat Score
39/100
Attack Intelligence
Open Ports Detected
21
Geographic Location
Country
China
City
Unknown
Region
Unknown
Coordinates
34.7732, 113.7220
Network Information
ASN
AS45090
Organization
Shenzhen Tencent Computer Systems Company Limited
Network
AS45090 Shenzhen Tencent Computer Systems Company Limited
WHOIS Information
inetnum
1.12.0.0 - 1.15.255.255
netname
TencentCloud
descr
China Internet Network Information Center
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-TENCENTCLOUD-CN
mnt-lower
MAINT-CNNIC-AP
mnt-routes
MAINT-CNNIC-AP
last-modified
2020-02-25T01:10:58Z
irt
IRT-TencentCloud-CN
address
District of Hi-tech Park, Shenzhen
e-mail
klayliang@tencent.com
abuse-mailbox
ipas@cnnic.cn
role
ABUSE CNNICCN
phone
+86-755-86013388-80224
nic-hdl
JX1747-AP
person
Jimmy Xiao
route
1.12.0.0/14
origin
AS45090
Attack Logs
| Date | Target Location | Protocol | Link |
|---|---|---|---|
| 2024-06-11 | Vultrmadrid | TELNET | View Log |
- Country: China
- Network: AS45090 shenzhen tencent computer systems company limited
- Noticed: 2 times
- Protocols Attacked: telnet
CVEs Detected
CVE-2007-2768 CVE-2008-3844 CVE-2016-20012 CVE-2017-15906 CVE-2018-15473 CVE-2018-15919 CVE-2018-20685 CVE-2019-6109 CVE-2019-6110 CVE-2019-6111 CVE-2020-14145 CVE-2020-15778 CVE-2021-36368 CVE-2021-41617 CVE-2023-38408 CVE-2023-48795 CVE-2023-51385 CVE-2023-51767
Disclaimer
This page contains threat intelligence information for the IPv4 address 1.14.190.102 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.