194.55.234.1 Threat Intelligence and Host Information

General

IP Address
194.55.234.1
IPv4 Address
Location
🇷🇺 Russia
RU
Network
AS34959
Kviktel LLC
Threat Score
15/100
Low Risk
Attack Intelligence
Open Ports Detected
123
Geographic Location
Country
Russia
City
Unknown
Region
Unknown
Coordinates
55.7386, 37.6068
Network Information
ASN
AS34959
Organization
Kviktel LLC
Network
AS34959 Kviktel LLC
WHOIS Information
inetnum
194.55.234.0 - 194.55.234.255
netname
PROCLOUD-NET
geoloc
55.65286 37.52862
geofeed
https://geofeed.procloud.ru/geofeed.csv
country
RU
admin-c
PN5242-RIPE
tech-c
PN5242-RIPE
status
ASSIGNED PA
mnt-by
ru-procloud-mnt
created
2019-10-29T07:53:30Z
last-modified
2021-02-10T10:40:21Z
role
PROCLOUD.RU NOC
address
117420 Moscow Russia
phone
+7 495 8333333
fax-no
+7 495 8333333
abuse-mailbox
abuse@procloud.ru
nic-hdl
PN5242-RIPE
route
194.55.234.0/23
descr
Procloud route
origin
AS34959

  • Country: Russia
  • Network:
  • Noticed: 1 times
  • Protocols Attacked: SSH

CVEs Detected

CVE-2009-0021 CVE-2009-0159 CVE-2009-3563 CVE-2013-5211 CVE-2014-9293 CVE-2014-9294 CVE-2014-9295 CVE-2014-9296 CVE-2014-9750 CVE-2014-9751 CVE-2015-1798 CVE-2015-1799 CVE-2015-7691 CVE-2015-7692 CVE-2015-7701 CVE-2015-7702 CVE-2015-7703 CVE-2015-7704 CVE-2015-7705 CVE-2015-7848 CVE-2015-7849 CVE-2015-7850 CVE-2015-7851 CVE-2015-7852 CVE-2015-7853 CVE-2015-7854 CVE-2015-7855 CVE-2015-7973 CVE-2015-7974 CVE-2015-7977 CVE-2016-2518 CVE-2016-4953 CVE-2016-4954 CVE-2016-4955 CVE-2016-4956 CVE-2017-6458 CVE-2018-7170 CVE-2019-8936 CVE-2020-11868 CVE-2020-13817

Disclaimer
This page contains threat intelligence information for the IPv4 address 194.55.234.1 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.