222.222.123.133 Threat Intelligence and Host Information
Jun 23, 2025
ipinfopage
General
IP Address
222.222.123.133
Location
🇨🇳 Beijing, China
Network
AS4134
Threat Score
43/100
Attack Intelligence
MITRE ATT&CK Techniques
T1110 - Brute Force
Open Ports Detected
23
Geographic Location
Country
China
City
Beijing
Region
Beijing
Coordinates
39.9075, 116.3972
Network Information
ASN
AS4134
Organization
Chinanet
Network
AS4134 Chinanet
WHOIS Information
inetnum
222.222.0.0 - 222.223.255.255
netname
CHINANET-HE
descr
Beijing 100032
country
CN
admin-c
CH93-AP
tech-c
CH93-AP
abuse-c
AC1573-AP
status
ALLOCATED PORTABLE
mnt-by
MAINT-CHINANET
mnt-lower
MAINT-CHINANET-HE
mnt-routes
MAINT-CHINANET-HE
mnt-irt
IRT-CHINANET-CN
last-modified
2022-02-28T06:53:44Z
irt
IRT-CHINANET-CN
address
100032
e-mail
anti-spam@chinatelecom.cn
abuse-mailbox
anti-spam@chinatelecom.cn
role
ABUSE CHINANETCN
phone
+86-10-58501724
nic-hdl
CH93-AP
person
Chinanet Hostmaster
fax-no
+86-10-58501724
Attack Logs
| Date | Target Location | Protocol | Link |
|---|---|---|---|
| 2025-06-22 | Warsaw, Poland | TELNET | View Log |
- Country: China
- Network:
- Noticed: 4 times
- Protocols Attacked: telnet
- Countries Attacked: Australia
CVEs Detected
CVE-2007-2768 CVE-2008-3844 CVE-2016-20012 CVE-2019-16905 CVE-2020-14145 CVE-2020-15778 CVE-2021-36368 CVE-2021-41617 CVE-2022-2048 CVE-2023-26048 CVE-2023-26049 CVE-2023-36478 CVE-2023-36479 CVE-2023-38408 CVE-2023-40167 CVE-2023-41900 CVE-2023-44487 CVE-2023-48795 CVE-2023-51385 CVE-2023-51767 CVE-2024-22201 CVE-2024-6763 CVE-2024-8184 CVE-2025-26465 CVE-2025-32728
Disclaimer
This page contains threat intelligence information for the IPv4 address 222.222.123.133 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.