167.86.73.135 Threat Intelligence - Germany | IP Address Lookup

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General

IP Address
167.86.73.135
IPv4 Address
Location
🇩🇪 Nuremberg, Germany
DE
Network
AS51167
Contabo GmbH
Threat Score
36/100
Medium Risk
blacklistbotnetcowriedionaeafatthoneytrapmailoneyMalicious IP
Attack Intelligence
Noticed
3 times
Protocols Attacked
mitre
Open Ports Detected
10000110200002122222225252533064434655358780993995
Geographic Location
Country
Germany
City
Nuremberg
Region
Bavaria
Coordinates
49.4050, 11.1617
Network Information
ASN
AS51167
Organization
Contabo GmbH
Network
AS51167 Contabo GmbH
WHOIS Information
NetRange
167.86.66.0 - 167.86.127.255
CIDR
167.86.80.0/20, 167.86.66.0/23, 167.86.96.0/19, 167.86.68.0/22, 167.86.72.0/21
NetName
RIPE
NetHandle
NET-167-86-66-0-1
Parent
NET167 (NET-167-0-0-0-0)
NetType
Early Registrations, Transferred to RIPE NCC
Organization
RIPE Network Coordination Centre (RIPE)
RegDate
2018-11-20
Updated
2025-02-10
Ref
https://rdap.arin.net/registry/ip/167.86.66.0
OrgName
RIPE Network Coordination Centre
OrgId
RIPE
Address
P.O. Box 10096
City
Amsterdam
PostalCode
1001EB
Country
NL
OrgTechHandle
RNO29-ARIN
OrgTechName
RIPE NCC Operations
OrgTechPhone
+31 20 535 4444
OrgTechEmail
hostmaster@ripe.net
OrgTechRef
https://rdap.arin.net/registry/entity/RNO29-ARIN
OrgAbuseHandle
ABUSE3850-ARIN
OrgAbuseName
Abuse Contact
OrgAbusePhone
+31205354444
Attack Logs
DateTarget LocationProtocolLink
2026-10-19 Cve 2021 42013 Attacker Ip List 2026 10 19 Multiple View Log
2026-10-19 Webexploit Mitre T1083 Ip List 2026 10 19 Multiple View Log
2026-10-19 Cve 2021 41773 Attacker Ip List 2026 10 19 Multiple View Log
2026-05-02 Cve 2024 4577 Attacker Ip List 2026 05 02 Multiple View Log
Disclaimer
This page contains threat intelligence information for the IPv4 address 167.86.73.135 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.