220.90.89.11 Threat Intelligence and Host Information

General

IP Address
220.90.89.11
IPv4 Address
Location
🇰🇷 Nam-gu, South Korea
KR
Network
AS4766
Korea Telecom
Threat Score
15/100
Low Risk
Attack Intelligence
Open Ports Detected
80
Geographic Location
Country
South Korea
City
Nam-gu
Region
Gwangju
Coordinates
35.1177, 126.9087
Network Information
ASN
AS4766
Organization
Korea Telecom
Network
AS4766 Korea Telecom
WHOIS Information
query
220.90.89.11
IPv4주소
220.90.89.0 - 220.90.89.127 (/25)
기관명
전남본부장
서비스명
KORNET
주소
광주광역시 광산구 산정동
우편번호
506255
할당일자
20020902
이름
IP주소 담당자
전화번호
+82-2-500-6631
전자우편
kornet_ip@kt.com
네트워크 구분
CUSTOMER
할당내역 등록일
20151129
IPv4 Address
220.90.89.0 - 220.90.89.127 (/25)
Organization Name
Jeonnambonbujang
Service Name
KORNET
Address
Sanjeong-Dong Gwangsan-Gu Gwangjugwangyeok-Si
Zip Code
506255
Registration Date
20151129
Name
IP Manager
Phone
+82-2-500-6631
E-Mail
kornet_ip@kt.com
Network Type
CUSTOMER

  • Country: South Korea
  • Network:
  • Noticed: 1 times
  • Protocols Attacked: Anonymous Proxy

CVEs Detected

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-2019-0190 CVE-2022-2097 CVE-2022-36760 CVE-2022-37436 CVE-2022-4304 CVE-2022-4450 CVE-2023-0215 CVE-2023-0286 CVE-2023-0464 CVE-2023-0465 CVE-2023-0466 CVE-2023-25690 CVE-2023-2650 CVE-2023-27522 CVE-2023-31122 CVE-2023-3817 CVE-2023-45802 CVE-2023-4807 CVE-2023-5678 CVE-2024-0727 CVE-2024-27316 CVE-2024-38474 CVE-2024-38475 CVE-2024-38476 CVE-2024-38477 CVE-2024-40898

Disclaimer
This page contains threat intelligence information for the IPv4 address 220.90.89.11 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.