103.217.145.104 Threat Intelligence and Host Information

General

IP Address
103.217.145.104
IPv4 Address
Location
Unknown
Network
AS
Threat Score
65/100
High Risk
atiffeedbanlistfeedbinarydefenseBrute-Forcbruteforce
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, T1595 - Active Scanning
Open Ports Detected
80
Geographic Location
Country
Unknown
City
Unknown
Region
Unknown
Coordinates
0.0000, 0.0000

Geographic coordinates not available for this IP.

Network Information
ASN
AS
Organization
Network
WHOIS Information
inetnum
103.217.144.0 - 103.217.145.255
netname
IDNIC-GBI-ID
descr
PT. GUNA BAHAN INTI
admin-c
APS33-AP
tech-c
APS33-AP
country
ID
mnt-by
MAINT-ID-GBI
mnt-irt
IRT-GBI-ID
mnt-routes
MAINT-ID-GBI
status
ASSIGNED PORTABLE
last-modified
2023-06-12T08:48:39Z
irt
IRT-GBI-ID
address
Sukabumi, Jawa Barat
e-mail
tech@gunabahan.my.id
abuse-mailbox
abuse@gunabahan.my.id
person
Alfian Pamungkas Sakawiguna
phone
+62-266-620073
nic-hdl
APS33-AP
route
103.217.145.0/24
origin
AS136052
Attack Logs
Date Target Location Protocol Link
2025-01-26 Perth, Australia MULTIPLE View Log

  • Country:
  • Network:
  • Noticed: 22 times
  • Protocols Attacked: ssh
  • Countries Attacked: Australia

CVEs Detected

CVE-2007-4723 CVE-2009-0796 CVE-2009-2299 CVE-2011-1176 CVE-2011-2688 CVE-2012-3526 CVE-2012-4001 CVE-2012-4360 CVE-2013-0941 CVE-2013-0942 CVE-2013-2765 CVE-2013-4365 CVE-2024-27316 CVE-2024-38474 CVE-2024-38476 CVE-2024-38477 CVE-2024-40898

Disclaimer
This page contains threat intelligence information for the IPv4 address 103.217.145.104 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.