122.114.252.177 Threat Intelligence and Host Information
Nov 19, 2024
ipinfopage
General
IP Address
122.114.252.177
Location
🇨🇳 China
Network
AS4837
Threat Score
15/100
Attack Intelligence
Open Ports Detected
123
Geographic Location
Country
China
City
Unknown
Region
Unknown
Coordinates
34.7732, 113.7220
Network Information
ASN
AS4837
Organization
CHINA UNICOM China169 Backbone
Network
AS4837 CHINA UNICOM China169 Backbone
WHOIS Information
inetnum
122.114.0.0 - 122.114.255.255
netname
ZZGIANT
descr
Room 703,Building 2,Xinghua Edifice, Hanghai Road, Jingkai District,Zhengzhou
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-ZZGIANT-CN
mnt-lower
MAINT-CNNIC-AP
mnt-routes
MAINT-CNNIC-AP
last-modified
2021-09-01T07:16:41Z
irt
IRT-ZZGIANT-CN
address
Room 703,Building 2,Xinghua Edifice, Hanghai Road, Jingkai District,Zhengzhou
e-mail
abuse@gainet.com
abuse-mailbox
ipas@cnnic.cn
role
ABUSE CNNICCN
phone
+86-18937119638
nic-hdl
YW7047-AP
person
Ren Yanjun
Attack Logs
| Date | Target Location | Protocol | Link |
|---|---|---|---|
| 2024-11-15 | Toronto, Canada | SSH | View Log |
- Country: China
- Network: AS4837 china unicom china169 backbone
- Noticed: 1 times
- Protocols Attacked: ssh
- Passive DNS Results: xxkdwl.com yinliu6666.com shop.runjia168.com abclm.cn mmxrcm.com
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 122.114.252.177 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.