167.94.138.132 Threat Intelligence and Host Information

General

IP Address
167.94.138.132
IPv4 Address
Location
🇺🇸 United States
US
Network
AS398324
CENSYS-ARIN-01
Threat Score
30/100
Low Risk
blacklistbotnetcybersecurityiockfsensormaliciousMalicious
Geographic Location
Country
United States
City
Unknown
Region
Unknown
Coordinates
37.7510, -97.8220
Network Information
ASN
AS398324
Organization
CENSYS-ARIN-01
Network
AS398324 CENSYS-ARIN-01
WHOIS Information
NetRange
167.94.138.0 - 167.94.138.255
CIDR
167.94.138.0/24
NetName
CENSY
NetHandle
NET-167-94-138-0-1
Parent
NET167 (NET-167-0-0-0-0)
NetType
Direct Allocation
OriginAS
Organization
Censys, Inc. (CENSY)
RegDate
2018-08-06
Updated
2019-08-03
Ref
https://rdap.arin.net/registry/entity/CENSY
OrgName
Censys, Inc.
OrgId
CENSY
Address
116 1/2 S Main Street
City
Ann Arbor
StateProv
MI
PostalCode
48104
Country
US
Comment
https://censys.io
OrgAbuseHandle
CAT20-ARIN
OrgAbuseName
Censys Abuse Team
OrgAbusePhone
+1-248-629-0125
OrgAbuseEmail
scan-abuse@censys.io
OrgAbuseRef
https://rdap.arin.net/registry/entity/CAT20-ARIN
Attack Logs
Date Target Location Protocol Link
2023-10-21 Digitaloceanlondon-Sip MULTIPLE View Log

  • Country: United States
  • Network: AS398324 censys inc.
  • Noticed: 1 times
  • Protcols Attacked: sip snmp
  • Countries Attacked: Canada, Czechia, Denmark, Estonia, France, Germany, Latvia, Lithuania, Norway, Poland, Romania, Turkey, Ukraine, United Kingdom of Great Britain and Northern Ireland, United States of America
  • Passive DNS Results: scanner-11.ch1.censys-scanner.com
Disclaimer
This page contains threat intelligence information for the IPv4 address 167.94.138.132 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.