52.80.22.106 Threat Intelligence and Host Information
Sep 24, 2024
ipinfopage
General
IP Address
52.80.22.106
Location
🇨🇳 Beijing, China
Network
AS55960
Threat Score
22/100
Attack Intelligence
MITRE ATT&CK Techniques
T1498 - Network Denial of Service
Open Ports Detected
22
Geographic Location
Country
China
City
Beijing
Region
Beijing
Coordinates
39.9285, 116.3850
Network Information
ASN
AS55960
Organization
Beijing Guanghuan Xinwang Digital
Network
AS55960 Beijing Guanghuan Xinwang Digital
WHOIS Information
NetRange
52.80.0.0 - 52.83.255.255
CIDR
52.80.0.0/14
NetName
APNIC
NetHandle
NET-52-80-0-0-1
Parent
NET52 (NET-52-0-0-0-0)
NetType
Early Registrations, Transferred to APNIC
OriginAS
Organization
Asia Pacific Network Information Centre (APNIC)
RegDate
Updated
2012-01-24
Ref
https://rdap.arin.net/registry/entity/APNIC
OrgName
Asia Pacific Network Information Centre
OrgId
APNIC
Address
PO Box 3646
City
South Brisbane
StateProv
QLD
PostalCode
4101
Country
AU
OrgAbuseHandle
AWC12-ARIN
OrgAbuseName
APNIC Whois Contact
OrgAbusePhone
+61 7 3858 3188
OrgAbuseEmail
search-apnic-not-arin@apnic.net
OrgAbuseRef
https://rdap.arin.net/registry/entity/AWC12-ARIN
OrgTechHandle
AWC12-ARIN
Attack Logs
| Date | Target Location | Protocol | Link |
|---|---|---|---|
| 2024-09-24 | Perth, Australia | MULTIPLE | View Log |
- Country: China
- Network: AS55960 beijing guanghuan xinwang digital
- Noticed: 1 times
- Protocols Attacked: SSH
- Passive DNS Results: aindecor.art
CVEs Detected
CVE-2007-2768 CVE-2008-3844 CVE-2016-20012 CVE-2021-36368 CVE-2021-41617 CVE-2023-38408 CVE-2023-48795 CVE-2023-51385 CVE-2023-51767 CVE-2024-6387
Disclaimer
This page contains threat intelligence information for the IPv4 address 52.80.22.106 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.