36.83.113.9 Threat Intelligence - Indonesia | IP Address Lookup

Share on:

General

IP Address
36.83.113.9
IPv4 Address
Location
🇮🇩 Tasikmalaya, Indonesia
ID
Network
AS7713
PT Telekomunikasi Indonesia
Threat Score
43/100
Medium Risk
aws-credentialsrevproxysuricatawazuhweb-exploit
Attack Intelligence
MITRE ATT&CK Techniques
T1046 - Network Service Scanning, T1595.001 - Scanning IP Blocks, T1595.002 - Vulnerability Scanning
Noticed
3 times
Protocols Attacked
aws
Countries Attacked
United Kingdom of Great Britain and Northern Ireland
Geographic Location
Country
Indonesia
City
Tasikmalaya
Region
West Java
Coordinates
-7.4967, 108.1413
Network Information
ASN
AS7713
Organization
PT Telekomunikasi Indonesia
Network
AS7713 PT Telekomunikasi Indonesia
Associated CVEs
WHOIS Information
inetnum
36.83.112.0 - 36.83.127.255
netname
TLKM_BB_SERVICE_36_83_DIVRE6-7
descr
PT TELKOM INDONESIA Menara Multimedia Lt.7 Jl. Kebon sirih No.12 JAKARTA
country
ID
admin-c
AZ163-AP
tech-c
FS370-AP
abuse-c
AI598-AP
status
ALLOCATED NON-PORTABLE
mnt-by
MAINT-TELKOMNET
mnt-lower
MAINT-TELKOMNET
mnt-routes
MAINT-TELKOMNET
mnt-irt
IRT-IDTELKOM-ID
last-modified
2021-01-26T22:07:08Z
irt
IRT-IDTELKOM-ID
address
PT. TELKOM INDONESIA
e-mail
abuse@telkom.co.id
abuse-mailbox
abuse@telkom.co.id
role
ABUSE IDTELKOMID
phone
+000000000
nic-hdl
AI598-AP
person
Akhmad Zaimi
route
36.83.113.0/24
origin
AS7713
Attack Logs
DateTarget LocationProtocolLink
2026-10-20 Webexploit Aws Credentials Ip List 2026 10 20 Multiple View Log
2026-10-20 Cve 2002 1149 Attacker Ip List 2026 10 20 Multiple View Log
Disclaimer
This page contains threat intelligence information for the IPv4 address 36.83.113.9 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.