103.113.171.119 Threat Intelligence - Indonesia | IP Address Lookup
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General
IP Address
103.113.171.119
Location
🇮🇩 Indonesia
Network
AS137352
Threat Score
30/100
Attack Intelligence
Noticed
10 times
Protocols Attacked
combined portscan ssh
Open Ports Detected
11014317012000212546558770718080818443993995
Geographic Location
Country
Indonesia
City
Unknown
Region
Unknown
Coordinates
-6.1750, 106.8286
Network Information
ASN
AS137352
Organization
PT. Cloudata Indonesia
Network
AS137352 PT. Cloudata Indonesia
WHOIS Information
inetnum
103.113.170.0 - 103.113.171.255
netname
IDNIC-CLOUDATA-ID
descr
PT. Cloudata Indonesia
admin-c
EIJ1-AP
tech-c
EIJ1-AP
country
ID
mnt-by
MNT-APJII-ID
mnt-irt
IRT-CLOUDATA-ID
mnt-routes
MAINT-ID-CLOUDATA
status
ASSIGNED PORTABLE
last-modified
2018-04-13T07:10:07Z
irt
IRT-CLOUDATA-ID
address
PT. CLOUDATA INDONESIA
e-mail
info@cloudata.co.id
abuse-mailbox
abuse@cloudata.id
person
Eddy Ismail Januar
phone
+62-21-7393366
nic-hdl
EIJ1-AP
fax-no
+62-21-7250945
route
103.113.171.0/24
origin
AS137352
Attack Logs
| Date | Target Location | Protocol | Link |
|---|---|---|---|
| 2026-09-04 | Digitaloceantoronto Combined | Multiple | View Log |
| 2026-09-04 | Toronto, Canada | SSH | View Log |
| 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 103.113.171.119 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.