107.189.28.96 Threat Intelligence - Luxembourg | IP Address Lookup
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General
IP Address
107.189.28.96
Location
🇱🇺 Luxembourg, Luxembourg
Network
AS53667
Threat Score
45/100
Attack Intelligence
MITRE ATT&CK Techniques
T1059 - Command and Scripting Interpreter, T1105 - Ingress Tool Transfer, T1110 - Brute Force
Noticed
6 times
Protocols Attacked
combined ssh
Countries Attacked
Australia, Finland, France, Germany, Poland, United States of America
Passive DNS
6figureslabs.com
Open Ports Detected
424250016881808094439993
Geographic Location
Country
Luxembourg
City
Luxembourg
Region
Luxembourg
Coordinates
49.7855, 6.1001
Network Information
ASN
AS53667
Organization
FranTech Solutions
Network
AS53667 FranTech Solutions
WHOIS Information
NetRange
107.189.0.0 - 107.189.31.255
CIDR
107.189.0.0/19
NetName
PONYNET-11
NetHandle
NET-107-189-0-0-1
Parent
NET107 (NET-107-0-0-0-0)
NetType
Direct Allocation
Organization
FranTech Solutions (SYNDI-5)
RegDate
2014-04-17
Updated
2014-04-17
Ref
https://rdap.arin.net/registry/ip/107.189.0.0
OrgName
FranTech Solutions
OrgId
SYNDI-5
Address
1621 Central Ave
City
Cheyenne
StateProv
WY
PostalCode
82001
Country
US
OrgAbuseHandle
FDI19-ARIN
OrgAbuseName
Dias, Francisco
OrgAbusePhone
+1-702-728-8933
OrgAbuseEmail
admin@frantech.ca
OrgAbuseRef
https://rdap.arin.net/registry/entity/FDI19-ARIN
OrgTechHandle
FDI19-ARIN
OrgTechName
Dias, Francisco
Attack Logs
| Date | Target Location | Protocol | Link |
|---|---|---|---|
| 2026-08-11 | Toronto, Canada | SSH | View Log |
| 2026-08-11 | Digitaloceantoronto Combined | Multiple | View Log |
Disclaimer
This page contains threat intelligence information for the IPv4 address 107.189.28.96 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.