41.215.144.73 Threat Intelligence and Host Information
Jun 19, 2024
ipinfopage
General
IP Address
41.215.144.73
Location
🇸🇿 Nhlangano, Eswatini
Network
AS19711
Threat Score
24/100
Attack Intelligence
MITRE ATT&CK Techniques
T1110 - Brute Force
Open Ports Detected
11
Geographic Location
Country
Eswatini
City
Nhlangano
Region
Shiselweni District
Coordinates
-27.1172, 31.2013
Network Information
ASN
AS19711
Organization
SWAZINET
Network
AS19711 SWAZINET
WHOIS Information
inetnum
41.215.144.0 - 41.215.147.255
netname
SPTC-IP-CORE
descr
Eswatini Telecom - retail block
country
SZ
admin-c
MT15-AFRINIC
tech-c
MT15-AFRINIC
status
ASSIGNED PA
mnt-by
TF-69-63-64-0-69-63-79-255-MNT
parent
41.215.144.0 - 41.215.159.255
person
Musa Tsela
address
Swaziland
phone
tel:+268-2405-2434
nic-hdl
MT15-AFRINIC
route
41.215.144.0/20
origin
AS19711
Attack Logs
| Date | Target Location | Protocol | Link |
|---|---|---|---|
| 2024-05-02 | London, UK | SSH | View Log |
- Country: Eswatini
- Network: AS19711 african network information center
- Noticed: 2 times
- Protocols Attacked: ssh
- Countries Attacked: Australia
Malware Detected on Host
Count: 1 623cff5dd85635ecbc471fc9fc21156bf7df12848cb5d3c384652b127b96a228
CVEs Detected
CVE-2007-2768 CVE-2008-3844 CVE-2010-4478 CVE-2010-4755 CVE-2010-5107 CVE-2011-4327 CVE-2011-5000 CVE-2012-0814 CVE-2014-1692 CVE-2014-2532 CVE-2014-2653 CVE-2015-5352 CVE-2015-5600 CVE-2015-6563 CVE-2015-6564 CVE-2016-0777 CVE-2016-10009 CVE-2016-10010 CVE-2016-10011 CVE-2016-10012 CVE-2016-10708 CVE-2016-1908 CVE-2016-20012 CVE-2016-3115 CVE-2017-15906 CVE-2018-15473 CVE-2018-20685 CVE-2019-6109 CVE-2019-6110 CVE-2019-6111 CVE-2020-15778 CVE-2021-36368 CVE-2023-38408 CVE-2023-48795 CVE-2023-51385 CVE-2023-51767
Disclaimer
This page contains threat intelligence information for the IPv4 address 41.215.144.73 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.