50.87.145.181 Threat Intelligence and Host Information

General

IP Address
50.87.145.181
IPv4 Address
Location
🇺🇸 United States
US
Network
AS46606
UNIFIEDLAYER-AS-1
Threat Score
15/100
Low Risk
Attack Intelligence
Open Ports Detected
110
Geographic Location
Country
United States
City
Unknown
Region
Unknown
Coordinates
37.7510, -97.8220
Network Information
ASN
AS46606
Organization
UNIFIEDLAYER-AS-1
Network
AS46606 UNIFIEDLAYER-AS-1
WHOIS Information
NetRange
50.87.0.0 - 50.87.255.255
CIDR
50.87.0.0/16
NetName
UNIFIEDLAYER-NETWORK-9
NetHandle
NET-50-87-0-0-1
Parent
NET50 (NET-50-0-0-0-0)
NetType
Direct Allocation
OriginAS
AS46606
Organization
Unified Layer (BLUEH-2)
RegDate
2006-08-08
Updated
2020-01-31
Ref
https://rdap.arin.net/registry/entity/BLUEH-2
OrgName
Unified Layer
OrgId
BLUEH-2
Address
1958 South 950 East
City
Provo
StateProv
UT
PostalCode
84606
Country
US
OrgNOCHandle
ENO74-ARIN
OrgNOCName
EIG Network Operations
OrgNOCPhone
+1-877-659-6181
OrgNOCEmail
eig-net-team@endurance.com
OrgNOCRef
https://rdap.arin.net/registry/entity/ENO74-ARIN
OrgTechHandle
ENO74-ARIN

Malware Detected on Host

Count: 1 35c1aed6141cadd2b50b8db77266b195e8dc490aae84e2c2b326ee7d688d3545

CVEs Detected

CVE-2010-4478 CVE-2010-4755 CVE-2010-5107 CVE-2011-4327 CVE-2011-5000 CVE-2012-0814 CVE-2014-1692 CVE-2014-2532 CVE-2014-2653 CVE-2015-5352 CVE-2015-5600 CVE-2015-6563 CVE-2015-6564 CVE-2016-0777 CVE-2016-10009 CVE-2016-10010 CVE-2016-10011 CVE-2016-10012 CVE-2016-10708 CVE-2016-1908 CVE-2016-20012 CVE-2017-15906 CVE-2018-15473 CVE-2018-20685 CVE-2019-6109 CVE-2019-6110 CVE-2019-6111 CVE-2020-15778 CVE-2021-36368 CVE-2023-38408

Disclaimer
This page contains threat intelligence information for the IPv4 address 50.87.145.181 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.