103.144.126.234 Threat Intelligence - Indonesia | IP Address Lookup

Share on:

General

IP Address
103.144.126.234
IPv4 Address
Location
🇮🇩 Jakarta, Indonesia
ID
Network
AS58369
PT. Fiber Networks Indonesia
Threat Score
35/100
Medium Risk
Aggressive-DetectionbruteforceBruteforceBrute-ForceConnection-Resetdigital oceanportscanProtocol-Probing
Attack Intelligence
Noticed
10 times
Protocols Attacked
combined portscan ssh
Open Ports Detected
11014320002225443465535877071808071993995
Geographic Location
Country
Indonesia
City
Jakarta
Region
Jakarta
Coordinates
-6.2114, 106.8446
Network Information
ASN
AS58369
Organization
PT. Fiber Networks Indonesia
Network
AS58369 PT. Fiber Networks Indonesia
WHOIS Information
inetnum
103.144.126.0 - 103.144.127.255
netname
IDNIC-RELIANCE-ID
descr
PT Reliance Sekuritas Indonesia, Tbk
admin-c
DD936-AP
tech-c
AYB1-AP
country
ID
mnt-by
MNT-APJII-ID
mnt-irt
IRT-RELIANCE-ID
mnt-routes
MAINT-ID-RELIANCE
status
ASSIGNED PORTABLE
last-modified
2019-10-24T04:32:33Z
irt
IRT-RELIANCE-ID
address
PT. Reliance Sekuritas Indonesia, Tbk
e-mail
noc@reliancesekuritas.com
abuse-mailbox
abuse@reliancesekuritas.com
person
Andy Yuniar Budimanto
phone
+62-21-6617768
nic-hdl
AYB1-AP
fax-no
+62-21-6619884
route
103.144.126.0/23
origin
AS139434
mnt-lower
MAINT-ID-RELIANCE
Attack Logs
DateTarget LocationProtocolLink
2026-09-03 Digitaloceantoronto Combined Multiple View Log
2026-09-03 Toronto, Canada SSH View Log
2026-09-02 Digitaloceantoronto Combined Multiple View Log
2026-09-02 Toronto, Canada SSH View Log
2026-09-01 Toronto, Canada SSH View Log
2026-09-01 Digitaloceantoronto Combined Multiple View Log
Disclaimer
This page contains threat intelligence information for the IPv4 address 103.144.126.234 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.