175.12.108.55 Threat Intelligence and Host Information
May 16, 2025
ipinfopage
General
IP Address
175.12.108.55
Location
🇨🇳 China
Network
AS4134
Threat Score
47/100
Attack Intelligence
MITRE ATT&CK Techniques
T1595 - Active Scanning
Open Ports Detected
22
Geographic Location
Country
China
City
Unknown
Region
Unknown
Coordinates
34.7732, 113.7220
Network Information
ASN
AS4134
Organization
Chinanet
Network
AS4134 Chinanet
WHOIS Information
inetnum
175.0.0.0 - 175.15.255.255
netname
CHINANET-HN
descr
Beijing 100032
country
CN
admin-c
CH632-AP
tech-c
CS499-AP
abuse-c
AC1573-AP
status
ALLOCATED PORTABLE
mnt-by
MAINT-CHINANET
mnt-lower
MAINT-CHINANET-HN
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
CHINANET HUNAN
phone
+86-10-58501724
nic-hdl
CH93-AP
fax-no
+86-10-58501724
person
Chinanet Hostmaster
Attack Logs
| Date | Target Location | Protocol | Link |
|---|---|---|---|
| 2025-05-16 | Warsaw, Poland | SSH | View Log |
- Country: China
- Network:
- Noticed: 7 times
- Protocols Attacked: ssh
- Countries Attacked: Australia
- Passive DNS Results: xcx.rrcfzd.com daikuan2.rrcfzd.com
Malware Detected on Host
Count: 2 e6d75c34c9e7618b89e6a8e9716fcf7c88267d2ba5941fc49cadd0bc818dfc18 9ddb1e8ead6758d0489860a7d6a5df1df54d4d28622af08d663a20f160726b95
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-2020-11022 CVE-2020-11023 CVE-2020-14145 CVE-2020-15778 CVE-2021-36368 CVE-2021-41617 CVE-2023-38408 CVE-2023-48795 CVE-2023-51385 CVE-2023-51767 CVE-2025-26465
Disclaimer
This page contains threat intelligence information for the IPv4 address 175.12.108.55 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.