114.80.36.40 Threat Intelligence and Host Information

General

IP Address
114.80.36.40
IPv4 Address
Location
🇨🇳 China
CN
Network
AS4812
China Telecom Group
Threat Score
45/100
Medium Risk
01.10.20252025abuseipdbAdbhoneyauto-generatedsecuritybotnetcisco
Attack Intelligence
MITRE ATT&CK Techniques
T1046 - Network Service Scanning
Open Ports Detected
22
Geographic Location
Country
China
City
Unknown
Region
Unknown
Coordinates
34.7732, 113.7220
Network Information
ASN
AS4812
Organization
China Telecom Group
Network
AS4812 China Telecom Group
WHOIS Information
inetnum
114.80.0.0 - 114.95.255.255
netname
CHINANET-SH
descr
Beijing 100032
country
CN
admin-c
CH93-AP
tech-c
CH93-AP
abuse-c
AC1573-AP
status
ALLOCATED PORTABLE
mnt-by
MAINT-CHINANET-SH
mnt-lower
MAINT-CHINANET-SH
mnt-irt
IRT-CHINANET-CN
last-modified
2023-02-07T08:25:17Z
irt
IRT-CHINANET-CN
address
Room 2405,357 Songlin Road,Shanghai 200122
e-mail
shizhiming.sh@chinatelecom.cn
abuse-mailbox
anti-spam@chinatelecom.cn
role
ABUSE CHINANETCN
phone
+86-21-68405784
nic-hdl
WWQ4-AP
person
Weng Wen Qian
fax-no
+86-21-50623458

  • Country: China
  • Network:
  • Noticed: 33 times
  • Protocols Attacked: web
  • Countries Attacked: Australia, Finland, France, Germany, Poland, United States of America

CVEs Detected

CVE-2007-2768 CVE-2008-3844 CVE-2016-20012 CVE-2017-15906 CVE-2018-15473 CVE-2018-15919 CVE-2018-20685 CVE-2019-6109 CVE-2019-6110 CVE-2019-6111 CVE-2020-14145 CVE-2020-15778 CVE-2021-36368 CVE-2021-41617 CVE-2023-38408 CVE-2023-48795 CVE-2023-51385 CVE-2023-51767 CVE-2025-26465 CVE-2025-32728

Disclaimer
This page contains threat intelligence information for the IPv4 address 114.80.36.40 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.