222.73.61.20 Threat Intelligence and Host Information

General

IP Address
222.73.61.20
IPv4 Address
Location
🇨🇳 China
CN
Network
AS4812
China Telecom Group
Threat Score
61/100
High Risk
auto-generatedsecuritybruteforceBruteforceBrute-Forcecowriemalicious
Attack Intelligence
MITRE ATT&CK Techniques
T1078 - Valid Accounts, T1083 - File and Directory Discovery, T1098.004 - SSH Authorized Keys, T1105 - Ingress Tool Transfer, T1110.004 - Credential Stuffing, T1110 - Brute Force
Open Ports Detected
10443
Geographic Location
Country
China
City
Unknown
Region
Unknown
Coordinates
34.7732, 113.7220
Network Information
ASN
AS4812
Organization
China Telecom Group
Network
AS4812 China Telecom Group
WHOIS Information
inetnum
222.64.0.0 - 222.73.255.255
netname
CHINANET-SH
descr
Beijing 100032
country
CN
admin-c
CH93-AP
tech-c
CH93-AP
abuse-c
AC1573-AP
status
ALLOCATED PORTABLE
mnt-by
MAINT-CHINANET-SH
mnt-lower
MAINT-CHINANET-SH
mnt-routes
MAINT-CHINANET-SH
mnt-irt
IRT-CHINANET-CN
last-modified
2014-02-27T08:51:31Z
irt
IRT-CHINANET-CN
address
Room 805,61 North Si Chuan Road,Shanghai,200085,PRC
e-mail
ipms@shtel.com.cn
abuse-mailbox
ip-admin@mail.online.sh.cn
role
ABUSE CHINANETCN
phone
+86-21-63630562
nic-hdl
XI5-AP
person
Wu Xiao Li
fax-no
+86-21-63630566
Attack Logs
Date Target Location Protocol Link
2025-01-15 London, UK SSH View Log

  • Country: China
  • Network:
  • Noticed: 8 times
  • Protocols Attacked: ssh
  • Countries Attacked: Australia, Poland, Sweden

Malware Detected on Host

Count: 1 e7b49cae30e5a3faa94b7cf0764f0b05289c9b5af9902ecb16ad97e6441e50f7

CVEs Detected

CVE-2021-23017 CVE-2021-3618 CVE-2023-44487

Disclaimer
This page contains threat intelligence information for the IPv4 address 222.73.61.20 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.