203.145.36.212 Threat Intelligence - Bangladesh | IP Address Lookup

Share on:

General

IP Address
203.145.36.212
IPv4 Address
Location
🇧🇩 Tongi, Bangladesh
BD
Network
AS141045
Civil Network
Threat Score
13/100
Low Risk
Attack Intelligence
Noticed
1 time
Protocols Attacked
fake mitre
Open Ports Detected
53
Geographic Location
Country
Bangladesh
City
Tongi
Region
Dhaka Division
Coordinates
23.8905, 90.3980
Network Information
ASN
AS141045
Organization
Civil Network
Network
AS141045 Civil Network
Associated CVEs
WHOIS Information
inetnum
203.145.36.0 - 203.145.37.255
netname
CIVILNETWORK-BD
descr
Civil Network
country
BD
org
ORG-CN17-AP
admin-c
CNA47-AP
tech-c
CNA47-AP
abuse-c
AC2748-AP
status
ALLOCATED PORTABLE
mnt-by
APNIC-HM
mnt-lower
MAINT-CIVILNETWORK-BD
mnt-routes
MAINT-CIVILNETWORK-BD
mnt-irt
IRT-CIVILNETWORK-BD
last-modified
2023-11-21T06:26:49Z
geoloc
23.9712782 90.2944576
irt
IRT-CIVILNETWORK-BD
address
Shardagonj, Kashimpur, Gazipur Dhaka 1346
e-mail
hena@civilnetworkbd.com
abuse-mailbox
hena@civilnetworkbd.com
organisation
ORG-CN17-AP
org-name
Civil Network
org-type
LIR
phone
+8801911702711
mnt-ref
APNIC-HM
Attack Logs
DateTarget LocationProtocolLink
2026-10-24 Webexploit Mitre T1593 Ip List 2026 10 24 Multiple View Log
2026-10-24 Webexploit Fake Googlebot Ip List 2026 10 24 Multiple View Log
2026-10-21 Webexploit Mitre T1593 Ip List 2026 10 21 Multiple View Log
2026-10-21 Webexploit Fake Googlebot Ip List 2026 10 21 Multiple View Log
2026-07-13 Webexploit Fake Googlebot Ip List 2026 07 13 Multiple View Log
2026-07-13 Webexploit Mitre T1593 Ip List 2026 07 13 Multiple View Log
Disclaimer
This page contains threat intelligence information for the IPv4 address 203.145.36.212 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.