173.249.3.108 Threat Intelligence and Host Information

General

IP Address
173.249.3.108
IPv4 Address
Location
🇩🇪 Nuremberg, Germany
DE
Network
AS51167
Contabo GmbH
Threat Score
27/100
Low Risk
portscanscannersvultr
Attack Intelligence
Open Ports Detected
143
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
173.249.0.0 - 173.249.63.255
CIDR
173.249.0.0/18
NetName
RIPE
NetHandle
NET-173-249-0-0-1
Parent
NET173 (NET-173-0-0-0-0)
NetType
Early Registrations, Transferred to RIPE NCC
OriginAS
Organization
RIPE Network Coordination Centre (RIPE)
RegDate
Updated
2013-07-29
Ref
https://rdap.arin.net/registry/entity/RIPE
OrgName
RIPE Network Coordination Centre
OrgId
RIPE
Address
P.O. Box 10096
City
Amsterdam
StateProv
PostalCode
1001EB
Country
NL
OrgAbuseHandle
ABUSE3850-ARIN
OrgAbuseName
Abuse Contact
OrgAbusePhone
+31205354444
OrgAbuseEmail
abuse@ripe.net
OrgAbuseRef
https://rdap.arin.net/registry/entity/ABUSE3850-ARIN
OrgTechHandle
RNO29-ARIN

CVEs Detected

CVE-2007-4723 CVE-2009-0796 CVE-2009-2299 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-2023-38709 CVE-2024-24795 CVE-2024-27316 CVE-2024-36387 CVE-2024-38472 CVE-2024-38473 CVE-2024-38474 CVE-2024-38475 CVE-2024-38476 CVE-2024-38477 CVE-2024-39573 CVE-2024-40898 CVE-2024-42516 CVE-2024-43204 CVE-2024-43394 CVE-2024-47252 CVE-2025-23048 CVE-2025-49630 CVE-2025-49812 CVE-2025-53020 CVE-2025-55753 CVE-2025-58098 CVE-2025-59775 CVE-2025-65082 CVE-2025-66200

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Disclaimer
This page contains threat intelligence information for the IPv4 address 173.249.3.108 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.