148.233.37.36 Threat Intelligence and Host Information

General

IP Address
148.233.37.36
IPv4 Address
Location
🇲🇽 Mexico City, Mexico
MX
Network
AS8151
Uninet S.A. de C.V.
Threat Score
32/100
Medium Risk
DDoSMaliciousIPRTBHauto-generatedsecurityblacklistbotnet
Attack Intelligence
MITRE ATT&CK Techniques
T1498 - Network Denial of Service
Geographic Location
Country
Mexico
City
Mexico City
Region
Mexico City
Coordinates
19.4499, -99.1731
Network Information
ASN
AS8151
Organization
Uninet S.A. de C.V.
Network
AS8151 Uninet S.A. de C.V.
WHOIS Information
NetRange
148.230.128.0 - 148.250.255.255
CIDR
148.230.128.0/17, 148.250.0.0/16, 148.248.0.0/15, 148.232.0.0/13, 148.240.0.0/13, 148.231.0.0/16
NetName
LACNIC-ERX-148-201-0-0
NetHandle
NET-148-230-128-0-1
Parent
NET148 (NET-148-0-0-0-0)
NetType
Transferred to LACNIC
OriginAS
Organization
Latin American and Caribbean IP address Regional Registry (LACNIC)
RegDate
2002-07-27
Updated
2018-03-15
Ref
https://rdap.arin.net/registry/entity/LACNIC
OrgName
Latin American and Caribbean IP address Regional Registry
OrgId
LACNIC
Address
Rambla Republica de Mexico 6125
City
Montevideo
StateProv
PostalCode
11400
Country
UY
OrgTechHandle
LACNIC-ARIN
OrgTechPhone
+598-2604-2222
OrgTechRef
https://rdap.arin.net/registry/entity/LACNIC-ARIN
OrgAbuseHandle
LWI100-ARIN
OrgAbusePhone
+598-2604-2222
OrgAbuseEmail
abuse@lacnic.net

  • Country: Mexico
  • Network:
  • Noticed: 1 times
  • Protocols Attacked: SSH
  • Countries Attacked: Italy, Poland

Similar IP Addresses Detected

148.233.111.232 148.233.136.213 148.233.37.42 148.233.37.43 148.233.37.49 148.233.37.59

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Disclaimer
This page contains threat intelligence information for the IPv4 address 148.233.37.36 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.