146.70.160.236 Threat Intelligence - Germany | IP Address Lookup

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General

IP Address
146.70.160.236
IPv4 Address
Location
🇩🇪 Frankfurt am Main, Germany
DE
Network
AS9009
M247 Europe SRL
Threat Score
35/100
Medium Risk
01.10.20252025cowrieDDoSdionaeafattHoneyNet Connecthoneytrap
Attack Intelligence
MITRE ATT&CK Techniques
T1498 - Network Denial of Service
Noticed
14 times
Protocols Attacked
wordpress
Countries Attacked
Finland, France, Germany, Malaysia, Poland, United States of America
Passive DNS
rallo2002.myds.me
Open Ports Detected
1443400074438443
Geographic Location
Country
Germany
City
Frankfurt am Main
Region
Hesse
Coordinates
50.1049, 8.6295
Network Information
ASN
AS9009
Organization
M247 Europe SRL
Network
AS9009 M247 Europe SRL
WHOIS Information
NetRange
146.70.0.0 - 146.70.255.255
CIDR
146.70.0.0/16
NetName
RIPE-ERX-146-70-0-0
NetHandle
NET-146-70-0-0-1
Parent
NET146 (NET-146-0-0-0-0)
NetType
Early Registrations, Transferred to RIPE NCC
Organization
RIPE Network Coordination Centre (RIPE)
RegDate
2004-02-04
Updated
2025-02-10
Ref
https://rdap.arin.net/registry/ip/146.70.0.0
OrgName
RIPE Network Coordination Centre
OrgId
RIPE
Address
P.O. Box 10096
City
Amsterdam
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
OrgTechName
RIPE NCC Operations
OrgTechPhone
+31 20 535 4444
Attack Logs
DateTarget LocationProtocolLink
2026-08-09 Webexploit Wo Multiple View Log
Additional Intelligence
Tor Exit Node
No
Malware Samples
1
Disclaimer
This page contains threat intelligence information for the IPv4 address 146.70.160.236 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.