78.94.115.49 Threat Intelligence and Host Information
Mar 31, 2025
ipinfopage
General
IP Address
78.94.115.49
IPv4 Address
Location
🇩🇪 Rüsselsheim am Main, Germany
DE
Network
AS3209
Vodafone GmbH
Threat Score
39/100
Medium Risk
Brute-ForcBruteforceBrute-ForceinfonoticeSSH
Geographic Location
Coordinates
49.9874, 8.4232
Network Information
Organization
Vodafone GmbH
Network
AS3209 Vodafone GmbH
Attack Logs
| Date |
Target Location |
Protocol |
Link |
| 2025-03-29 |
Toronto, Canada |
SSH |
View Log |
- Country: Germany
- Network:
- Noticed: 2 times
- Protocols Attacked: ssh
CVEs Detected
CVE-2006-20001
CVE-2007-4723
CVE-2008-0455
CVE-2009-0796
CVE-2009-2299
CVE-2011-1176
CVE-2011-2688
CVE-2012-0883
CVE-2012-2687
CVE-2012-3499
CVE-2012-3526
CVE-2012-4001
CVE-2012-4360
CVE-2012-4558
CVE-2013-0941
CVE-2013-0942
CVE-2013-1862
CVE-2013-1896
CVE-2013-2765
CVE-2013-4365
CVE-2013-5704
CVE-2013-6438
CVE-2014-0098
CVE-2014-0118
CVE-2014-0226
CVE-2014-0231
CVE-2015-0228
CVE-2015-3183
CVE-2016-4975
CVE-2016-5387
CVE-2016-8612
CVE-2016-8743
CVE-2017-3167
CVE-2017-3169
CVE-2017-7679
CVE-2017-9788
CVE-2017-9798
CVE-2018-1301
CVE-2018-1302
CVE-2018-1303
CVE-2021-32785
CVE-2021-32786
CVE-2021-32791
CVE-2021-32792
CVE-2021-34798
CVE-2021-39275
CVE-2021-40438
CVE-2021-44790
CVE-2022-22719
CVE-2022-22720
CVE-2022-22721
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-2023-25690
CVE-2023-27522
CVE-2023-31122
CVE-2023-45802
CVE-2024-27316
CVE-2024-38474
CVE-2024-38476
CVE-2024-38477
CVE-2024-40898
Disclaimer
This page contains threat intelligence information for the IPv4 address 78.94.115.49 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.