103.101.224.137 Threat Intelligence and Host Information

General

IP Address
103.101.224.137
IPv4 Address
Location
🇮🇩 Indonesia
ID
Network
AS134612
PT Atria Teknologi Indonesia
Threat Score
17/100
Low Risk
Attack Intelligence
Open Ports Detected
110
Geographic Location
Country
Indonesia
City
Unknown
Region
Unknown
Coordinates
-6.1728, 106.8272
Network Information
ASN
AS134612
Organization
PT Atria Teknologi Indonesia
Network
AS134612 PT Atria Teknologi Indonesia
WHOIS Information
inetnum
103.101.224.0 - 103.101.227.255
netname
IDNIC-INTERNUSA-ID
descr
Jakarta timur, DKI Jakarta, 10570
admin-c
LN441-AP
tech-c
LN441-AP
country
ID
mnt-by
MNT-APJII-ID
mnt-routes
MAINT-ID-INTERNUSA
mnt-irt
IRT-INTERNUSA-ID
status
ASSIGNED PORTABLE
last-modified
2017-09-19T06:52:15Z
irt
IRT-INTERNUSA-ID
address
Jakarta timur,DKI Jakarta, 10570
e-mail
IT-Admin@internusa.co.id
abuse-mailbox
IT-Admin@internusa.co.id
person
Lukman Nurhakim
phone
+62-21-285652
nic-hdl
LN441-AP

  • Country: Indonesia
  • Network: AS134612 pt atria teknologi indonesia
  • Noticed: 1 times
  • Protcols Attacked: SSH
  • Passive DNS Results: circle-database-system.com www.circle-database-system.com etools-gdforce.com backup-msa-lama.com

CVEs Detected

CVE-2010-4478 CVE-2010-4755 CVE-2010-5107 CVE-2011-4327 CVE-2011-5000 CVE-2012-0814 CVE-2014-1692 CVE-2014-2532 CVE-2014-2653 CVE-2015-5352 CVE-2015-5600 CVE-2015-6563 CVE-2015-6564 CVE-2016-0777 CVE-2016-10009 CVE-2016-10010 CVE-2016-10011 CVE-2016-10012 CVE-2016-10708 CVE-2016-1908 CVE-2016-20012 CVE-2017-15906 CVE-2017-9118 CVE-2017-9120 CVE-2018-15473 CVE-2018-20685 CVE-2019-6109 CVE-2019-6110 CVE-2019-6111 CVE-2020-15778 CVE-2021-21703 CVE-2021-21704 CVE-2021-21705 CVE-2021-21706 CVE-2021-21707 CVE-2021-21708 CVE-2021-36368 CVE-2022-31625 CVE-2022-31626 CVE-2022-31628 CVE-2022-31629 CVE-2022-31630 CVE-2022-37454 CVE-2023-38408

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Disclaimer
This page contains threat intelligence information for the IPv4 address 103.101.224.137 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.