103.148.165.50 Threat Intelligence - India | IP Address Lookup
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General
IP Address
103.148.165.50
Location
🇮🇳 Noida, India
Network
AS134286
Threat Score
35/100
Attack Intelligence
Noticed
10 times
Protocols Attacked
combined portscan ssh
Open Ports Detected
1432570718443995
Geographic Location
Country
India
City
Noida
Region
Uttar Pradesh
Coordinates
28.5759, 77.3345
Network Information
ASN
AS134286
Organization
Net for Choice
Network
AS134286 Net for Choice
WHOIS Information
inetnum
103.148.165.0 - 103.148.165.255
netname
SYSTOOL6754
descr
Systools Software Private Limited
admin-c
AKS107-AP
tech-c
AKS107-AP
country
IN
mnt-by
MAINT-IN-IRINN
mnt-routes
MAINT-IN-SYSTOOL6754
mnt-irt
IRT-SYSTOOL6754-IN
status
ASSIGNED PORTABLE
last-modified
2025-08-11T22:50:33Z
irt
IRT-SYSTOOL6754-IN
address
UNIT NO-528 CITI CENTER,OPP.SEC-12 METRO STATION,SECTOR-12 DWARKA,,New Delhi,Delhi-110075
e-mail
internet@systoolsgroup.com
abuse-mailbox
internet@systoolsgroup.com
person
Anuraag Kumar Singh
phone
+91 01128084986
nic-hdl
AKS107-AP
route
103.148.165.0/24
origin
AS134286
Attack Logs
| Date | Target Location | Protocol | Link |
|---|---|---|---|
| 2026-09-04 | Digitaloceantoronto Combined | Multiple | View Log |
| 2026-09-04 | Toronto, Canada | SSH | View Log |
| 2026-09-03 | Digitaloceantoronto Combined | Multiple | View Log |
| 2026-09-03 | Toronto, Canada | SSH | View Log |
| 2026-09-02 | Digitaloceantoronto Combined | Multiple | View Log |
| 2026-09-02 | Toronto, Canada | SSH | View Log |
| 2026-09-01 | Toronto, Canada | SSH | View Log |
| 2026-09-01 | Digitaloceantoronto Combined | Multiple | View Log |
Disclaimer
This page contains threat intelligence information for the IPv4 address 103.148.165.50 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.