103.187.9.13 Threat Intelligence - Indonesia | IP Address Lookup

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General

IP Address
103.187.9.13
IPv4 Address
Location
🇮🇩 Indonesia
ID
Network
AS150546
Dinas Komunikasi dan Informatika Kabupat...
Threat Score
50/100
Medium Risk
automatedbrute-forcebruteforcecowriedigital oceandionaeafatthoneytrap
Attack Intelligence
MITRE ATT&CK Techniques
T1059 - Command and Scripting Interpreter, T1105 - Ingress Tool Transfer, T1190 - Exploit Public-Facing Application
Noticed
11 times
Protocols Attacked
combined portscan ssh
Passive DNS
disdik.kedirikab.go.id
Open Ports Detected
44380800081820090909100
Geographic Location
Country
Indonesia
City
Unknown
Region
Unknown
Coordinates
-6.1750, 106.8286
Network Information
ASN
AS150546
Organization
Dinas Komunikasi dan Informatika Kabupaten Kediri
Network
AS150546 Dinas Komunikasi dan Informatika Kabupaten Kediri
Associated CVEs
WHOIS Information
inetnum
103.187.9.0 - 103.187.9.255
netname
IDNIC-DISKOMINFOKABKDR-ID
descr
Dinas Komunikasi dan Informatika Kabupaten Kediri
admin-c
FBA7-AP
tech-c
FBA7-AP
country
ID
mnt-by
MNT-APJII-ID
mnt-lower
MNT-APJII-ID
mnt-routes
MNT-APJII-ID
mnt-irt
IRT-IDNIC-ID
status
ALLOCATED PORTABLE
last-modified
2023-02-13T11:17:44Z
irt
IRT-IDNIC-ID
address
INDONESIA NETWORK INFORMATION CENTER
e-mail
abuse@idnic.net
abuse-mailbox
abuse@idnic.net
person
Faisal Budi Aji
phone
+62-354-682152
nic-hdl
FBA7-AP
Attack Logs
DateTarget LocationProtocolLink
2026-09-01 Toronto, Canada SSH View Log
2026-09-01 Vultrtokyo SSH View Log
2026-09-01 Vultrtokyo Combined Multiple View Log
2026-09-01 Digitaloceantoronto Combined Multiple View Log
Disclaimer
This page contains threat intelligence information for the IPv4 address 103.187.9.13 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.