103.19.190.92 Threat Intelligence and Host Information
May 03, 2024
ipinfopage
General
IP Address
103.19.190.92
Location
🇭🇰 Hong Kong
Network
AS38197
Threat Score
41/100
Attack Intelligence
MITRE ATT&CK Techniques
T1110 - Brute Force
Open Ports Detected
1883
Geographic Location
Country
Hong Kong
City
Unknown
Region
Unknown
Coordinates
22.2578, 114.1657
Network Information
ASN
AS38197
Organization
Sun Network Hong Kong Limited - HongKong Backbone
Network
AS38197 Sun Network Hong Kong Limited - HongKong Backbone
WHOIS Information
inetnum
103.19.190.64 - 103.19.190.95
netname
SNIG-HK
descr
Sun Network International Group
country
HK
admin-c
SNIG1-AP
tech-c
SNIG1-AP
abuse-c
AG910-AP
status
ALLOCATED NON-PORTABLE
mnt-by
MAINT-SNIGL-HK
mnt-irt
IRT-GELTD-HK
last-modified
2014-09-04T14:33:42Z
irt
IRT-GELTD-HK
address
3/F, Trans Asia Ctr, 18 Kin Hong St, Kwai Chung
e-mail
SNIGL@SNW.HK
abuse-mailbox
IPADMIN@10GE.HK
role
Sun Network International Group Limited administra
phone
+852-62767824
nic-hdl
SNIG1-AP
Attack Logs
| Date | Target Location | Protocol | Link |
|---|---|---|---|
| 2024-04-30 | Warsaw, Poland | SSH | View Log |
- Country: Hong Kong
- Network: AS64050 bgpnet global asn
- Noticed: 3 times
- Protocols Attacked: ssh
- Countries Attacked: Australia, Poland
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-2023-51384 CVE-2023-51385 CVE-2023-51767
Disclaimer
This page contains threat intelligence information for the IPv4 address 103.19.190.92 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.