51.161.162.2 Threat Intelligence - Australia | IP Address Lookup
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General
IP Address
51.161.162.2
Location
🇦🇺 Sydney, Australia
Network
AS16276
Threat Score
7/100
Attack Intelligence
Noticed
1 time
Protocols Attacked
mitre php webshell
Geographic Location
Country
Australia
City
Sydney
Region
New South Wales
Coordinates
-33.8672, 151.1997
Network Information
ASN
AS16276
Organization
OVH SAS
Network
AS16276 OVH SAS
Associated CVEs
Attack Logs
| Date | Target Location | Protocol | Link |
|---|---|---|---|
| 2026-10-25 | Cve 2002 0953 Attacker Ip List 2026 10 25 | Multiple | View Log |
| 2026-10-21 | Cve 2002 0953 Attacker Ip List 2026 10 21 | Multiple | View Log |
| 2026-10-20 | Cve 2002 0953 Attacker Ip List 2026 10 20 | Multiple | View Log |
| 2026-10-20 | Webexploit Mitre T1190 Ip List 2026 10 20 | Multiple | View Log |
| 2021-11-05 | Webexploit Php Version Recon Ip List 2021 11 05 | Multiple | View Log |
| 2021-11-05 | Webexploit Webshell Filename Probe Ip List 2021 11 05 | Multiple | View Log |
| 2021-11-01 | Webexploit Php Version Recon Ip List 2021 11 01 | Multiple | View Log |
| 2021-11-01 | Webexploit Webshell Filename Probe Ip List 2021 11 01 | Multiple | View Log |
| 2021-09-28 | Webexploit Php Version Recon Ip List 2021 09 28 | Multiple | View Log |
| 2021-09-28 | Webexploit Webshell Filename Probe Ip List 2021 09 28 | Multiple | View Log |
| 2021-09-15 | Webexploit Php Version Recon Ip List 2021 09 15 | Multiple | View Log |
| 2021-09-14 | Webexploit Php Version Recon Ip List 2021 09 14 | Multiple | View Log |
| 2021-09-14 | Webexploit Webshell Filename Probe Ip List 2021 09 14 | Multiple | View Log |
Disclaimer
This page contains threat intelligence information for the IPv4 address 51.161.162.2 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.