104.37.185.2 Threat Intelligence - United States | IP Address Lookup
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General
IP Address
104.37.185.2
Location
🇺🇸 United States
Network
AS19318
Threat Score
37/100
Attack Intelligence
MITRE ATT&CK Techniques
T1110 - Brute Force, T1190 - Exploit Public-Facing Application
Noticed
2 times
Protocols Attacked
web
Countries Attacked
China, Germany, Russian Federation, Türkiye, United Kingdom of Great Britain and Northern Ireland, United States of America
Passive DNS
hkkillop.website
Open Ports Detected
228080
Geographic Location
Country
United States
City
Unknown
Region
Unknown
Coordinates
37.7510, -97.8220
Network Information
ASN
AS19318
Organization
Interserver, Inc
Network
AS19318 Interserver, Inc
Associated CVEs
WHOIS Information
NetRange
104.37.184.0 - 104.37.191.255
CIDR
104.37.184.0/21
NetName
INTERSERVER
NetHandle
NET-104-37-184-0-1
Parent
NET104 (NET-104-0-0-0-0)
NetType
Direct Allocation
Organization
Interserver, Inc (INTER-83)
RegDate
2014-06-18
Updated
2014-06-18
Comment
Please use abusencc@interserver.net for all abuse reports.
Ref
https://rdap.arin.net/registry/ip/104.37.184.0
OrgName
Interserver, Inc
OrgId
INTER-83
Address
110 Meadowlands Pkwy
City
Secaucus
StateProv
NJ
PostalCode
07094
Country
US
OrgTechHandle
NOC1390-ARIN
OrgTechName
Network Operations Center
OrgTechPhone
+1-201-605-1440
OrgTechEmail
abusencc@interserver.net
OrgTechRef
https://rdap.arin.net/registry/entity/NOC1390-ARIN
OrgAbuseHandle
NOC1390-ARIN
Attack Logs
| Date | Target Location | Protocol | Link |
|---|---|---|---|
| 2026-10-17 | Cfglobal Web | Multiple | View Log |
Additional Intelligence
Threat Feeds / IP Sets
- hphosts_emd
Disclaimer
This page contains threat intelligence information for the IPv4 address 104.37.185.2 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.