69.164.215.90 Threat Intelligence and Host Information

General

IP Address
69.164.215.90
IPv4 Address
Location
🇺🇸 Cedar Knolls, United States
US
Network
AS63949
Linode, LLC
Threat Score
39/100
Medium Risk
cowriehoneytrapLAMPmalicioussftpssh
Attack Intelligence
Open Ports Detected
123
Geographic Location
Country
United States
City
Cedar Knolls
Region
New Jersey
Coordinates
40.8229, -74.4592
Network Information
ASN
AS63949
Organization
Linode, LLC
Network
AS63949 Linode, LLC
WHOIS Information
NetRange
69.164.192.0 - 69.164.223.255
CIDR
69.164.192.0/19
NetName
LINODE
NetHandle
NET-69-164-192-0-2
Parent
LINODE-US (NET-69-164-192-0-1)
NetType
Reassigned
OriginAS
Organization
Linode (LINOD)
RegDate
2008-04-24
Updated
2022-12-15
Comment
http://www.linode.com
Ref
https://rdap.arin.net/registry/entity/LINOD
OrgName
Linode
OrgId
LINOD
Address
249 Arch St
City
Philadelphia
StateProv
PA
PostalCode
19106
Country
US
OrgAbuseHandle
LAS12-ARIN
OrgAbuseName
Linode Abuse Support
OrgAbusePhone
+1-609-380-7100
OrgAbuseEmail
abuse@linode.com
OrgAbuseRef
https://rdap.arin.net/registry/entity/LAS12-ARIN
Attack Logs
Date Target Location Protocol Link
2025-08-03 London, UK SSH View Log

  • Country: United States
  • Network:
  • Noticed: 2 times
  • Protocols Attacked: ssh
  • Passive DNS Results: buildadam.com notpowerless.com

Malware Detected on Host

Count: 1 93a644ebd2d48832aa747966a4b06ca2f52907f931f683d50b4c8d99ee3b3a5c

CVEs Detected

CVE-2004-0179 CVE-2006-20001 CVE-2007-4723 CVE-2009-0796 CVE-2009-1390 CVE-2009-2299 CVE-2009-3765 CVE-2009-3766 CVE-2009-3767 CVE-2011-1176 CVE-2011-2688 CVE-2012-3526 CVE-2012-4001 CVE-2012-4360 CVE-2013-0941 CVE-2013-0942 CVE-2013-2765 CVE-2013-4365 CVE-2016-1546 CVE-2016-2105 CVE-2016-2106 CVE-2016-2107 CVE-2016-2109 CVE-2016-2167 CVE-2016-2168 CVE-2016-2176 CVE-2016-2177 CVE-2016-2178 CVE-2016-2179 CVE-2016-2180 CVE-2016-2181 CVE-2016-2182 CVE-2016-4975 CVE-2016-4979 CVE-2016-5387 CVE-2016-6302 CVE-2016-6303 CVE-2016-7055 CVE-2016-8610 CVE-2016-8612 CVE-2016-8734 CVE-2016-8740 CVE-2016-8743 CVE-2017-15710 CVE-2017-15715 CVE-2017-3167 CVE-2017-3169 CVE-2017-3736 CVE-2017-3737 CVE-2017-3738 CVE-2017-7679 CVE-2017-9788 CVE-2017-9798 CVE-2017-9800 CVE-2018-0732 CVE-2018-0734 CVE-2018-0737 CVE-2018-0739 CVE-2018-11763 CVE-2018-11782 CVE-2018-1283 CVE-2018-1301 CVE-2018-1302 CVE-2018-1303 CVE-2018-1312 CVE-2018-1333 CVE-2018-17189 CVE-2018-17199 CVE-2018-5407 CVE-2019-0196 CVE-2019-0203 CVE-2019-0211 CVE-2019-0217 CVE-2019-0220 CVE-2019-10082 CVE-2019-10092 CVE-2019-10098 CVE-2019-1547 CVE-2019-1551 CVE-2019-1552 CVE-2019-1559 CVE-2019-1563 CVE-2019-17567 CVE-2020-11985 CVE-2020-13938 CVE-2020-17525 CVE-2020-1927 CVE-2020-1934 CVE-2020-1968 CVE-2020-1971 CVE-2020-35452 CVE-2021-23840 CVE-2021-23841 CVE-2021-26690 CVE-2021-26691 CVE-2021-32785 CVE-2021-32786 CVE-2021-32791 CVE-2021-32792 CVE-2021-33193 CVE-2021-34798 CVE-2021-3712 CVE-2021-39275 CVE-2021-40438 CVE-2021-4160 CVE-2021-44224 CVE-2021-44790 CVE-2022-0778 CVE-2022-1292 CVE-2022-2068 CVE-2022-22719 CVE-2022-22720 CVE-2022-22721 CVE-2022-23943 CVE-2022-26377 CVE-2022-28330 CVE-2022-28614 CVE-2022-28615 CVE-2022-29404 CVE-2022-30556 CVE-2022-31813 CVE-2022-36760 CVE-2022-37436 CVE-2022-4304 CVE-2023-0215 CVE-2023-0286 CVE-2023-0464 CVE-2023-0465 CVE-2023-0466 CVE-2023-25690 CVE-2023-2650 CVE-2023-31122 CVE-2023-3817 CVE-2023-38709 CVE-2023-45802 CVE-2023-5678 CVE-2024-0727 CVE-2024-24795 CVE-2024-27316 CVE-2024-38472 CVE-2024-38473 CVE-2024-38474 CVE-2024-38475 CVE-2024-38476 CVE-2024-38477 CVE-2024-39573 CVE-2024-40898 CVE-2024-42516 CVE-2024-43204 CVE-2024-43394 CVE-2024-45720 CVE-2024-46901 CVE-2024-47252 CVE-2025-49812 CVE-2025-53020

Disclaimer
This page contains threat intelligence information for the IPv4 address 69.164.215.90 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.