116.197.131.180 Threat Intelligence - Indonesia | IP Address Lookup

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General

IP Address
116.197.131.180
IPv4 Address
Location
🇮🇩 Jakarta, Indonesia
ID
Network
AS58369
PT. Fiber Networks Indonesia
Threat Score
5/100
Low Risk
Attack Intelligence
Protocols Attacked
combined portscan ssh
Open Ports Detected
1701172344346558780993995
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
116.197.131.0 - 116.197.131.255
netname
FIBERNET-NETBLOCK
descr
FIBERNET
country
ID
admin-c
NF108-AP
tech-c
NF108-AP
status
ALLOCATED NON-PORTABLE
notify
admin@fiber.net.id
mnt-by
MAINT-FIBERNET-ID
mnt-lower
MAINT-FIBERNET-ID
mnt-routes
MAINT-FIBERNET-ID
mnt-irt
IRT-FIBERNET-ID
geoloc
-6.3081695 106.8369562
last-modified
2024-10-07T09:44:40Z
irt
IRT-FIBERNET-ID
address
Rukan Tanjung Mas Raya Blok B1. No. 5, Jagakarsa, Jakarta, Indonesia
e-mail
admin@fiber.net.id
abuse-mailbox
abuse@fiber.net.id
role
NOC FIBERNET
phone
+62-21-7532726
nic-hdl
NF108-AP
route
116.197.128.0/21
origin
AS58369
Attack Logs
DateTarget LocationProtocolLink
2026-08-31 Digitaloceantoronto Combined Multiple View Log
2026-08-31 Toronto, Canada SSH View Log
2026-08-30 Toronto, Canada SSH View Log
2026-08-30 Digitaloceantoronto Combined Multiple View Log
2026-08-29 Digitaloceantoronto Combined Multiple View Log
2026-08-29 Toronto, Canada SSH View Log
2026-08-28 Digitaloceantoronto Combined Multiple View Log
2026-08-28 Toronto, Canada SSH View Log
Disclaimer
This page contains threat intelligence information for the IPv4 address 116.197.131.180 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.