45.169.7.33 Threat Intelligence - Brazil | IP Address Lookup

Share on:

General

IP Address
45.169.7.33
IPv4 Address
Location
🇧🇷 Nova Iguaçu, Brazil
BR
Network
AS268080
JMA PROVEDOR DE INTERNET LTDA - ME
Threat Score
5/100
Low Risk
Attack Intelligence
Noticed
1 time
Protocols Attacked
fake mitre
Open Ports Detected
2332
Geographic Location
Country
Brazil
City
Nova Iguaçu
Region
Rio de Janeiro
Coordinates
-22.7539, -43.4519
Network Information
ASN
AS268080
Organization
JMA PROVEDOR DE INTERNET LTDA - ME
Network
AS268080 JMA PROVEDOR DE INTERNET LTDA - ME
WHOIS Information
inetnum
45.169.4.0/22
aut-num
AS268080
abuse-c
ALPCA234
owner
JMA PROVEDOR DE INTERNET LTDA - ME
ownerid
10.806.734/0001-16
responsible
ALAN PEREIRA CARVALHO
country
BR
owner-c
ALPCA234
tech-c
ALPCA234
inetrev
45.169.4.0/22
nserver
ns1.jmafibra.com.br [lame - not published]
nsstat
20261024 UH
nslastaa
20250515
dsinetrev
45.169.4.0/24
dsrecord
40460 RSA-SHA-256 2C231F71C559EFDB3F29003D742F846FE7BC8344FCBB26B3EBF9E9DA49059A6F
dsstatus
20261024 OK
dslastok
20261024
created
20181214
changed
20181214
nic-hdl-br
ALPCA234
person
ALAN PEREIRA CARVALHO
e-mail
suporte@jmatelecom.com.br
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
2026-07-16 Webexploit Mitre T1593 Ip List 2026 07 16 Multiple View Log
2026-07-16 Webexploit Fake Googlebot Ip List 2026 07 16 Multiple View Log
Disclaimer
This page contains threat intelligence information for the IPv4 address 45.169.7.33 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.