118.34.4.196 Threat Intelligence and Host Information

General

IP Address
118.34.4.196
IPv4 Address
Location
🇰🇷 Chungcheongnam-do, South Korea
KR
Network
AS4766
Korea Telecom
Threat Score
15/100
Low Risk
Attack Intelligence
Open Ports Detected
443
Geographic Location
Country
South Korea
City
Chungcheongnam-do
Region
Chungcheongnam-do
Coordinates
36.5030, 127.0028
Network Information
ASN
AS4766
Organization
Korea Telecom
Network
AS4766 Korea Telecom
WHOIS Information
query
118.34.4.196
IPv4주소
118.34.4.0 - 118.34.4.255 (/24)
기관명
(주) 케이티
서비스명
KORNET
주소
대전광역시 중구 문화1동
우편번호
301131
할당일자
20070803
이름
IP주소 담당자
전화번호
+82-2-500-6631
전자우편
kornet_ip@kt.com
네트워크 구분
CUSTOMER
할당내역 등록일
20161001
IPv4 Address
118.34.4.0 - 118.34.4.255 (/24)
Organization Name
KT
Service Name
KORNET
Address
Munhwa1-Dong Jung-Gu Daejeongwangyeok-Si
Zip Code
301131
Registration Date
20161001
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-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-2022-3996 CVE-2022-4203 CVE-2022-4304 CVE-2022-4450 CVE-2023-0215 CVE-2023-0216 CVE-2023-0217 CVE-2023-0286 CVE-2023-0401 CVE-2023-0464 CVE-2023-0465 CVE-2023-0466 CVE-2023-1255 CVE-2023-2650 CVE-2023-2975 CVE-2023-3817 CVE-2023-4807 CVE-2023-5363 CVE-2023-5678 CVE-2023-6129 CVE-2024-0727

Disclaimer
This page contains threat intelligence information for the IPv4 address 118.34.4.196 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.