148.204.110.113 Threat Intelligence - Mexico | IP Address Lookup
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General
IP Address
148.204.110.113
Location
🇲🇽 Gustavo Adolfo Madero, Mexico
Network
AS3484
Threat Score
35/100
Attack Intelligence
Noticed
7 times
Protocols Attacked
combined portscan
Countries Attacked
China, Germany, Russian Federation, United Kingdom of Great Britain and Northern Ireland, United States of America
Geographic Location
Country
Mexico
City
Gustavo Adolfo Madero
Region
Mexico City
Coordinates
19.5045, -99.1172
Network Information
ASN
AS3484
Organization
Instituto Politecnico Nacional
Network
AS3484 Instituto Politecnico Nacional
WHOIS Information
NetRange
148.201.0.0 - 148.221.255.255
CIDR
148.208.0.0/13, 148.220.0.0/15, 148.202.0.0/15, 148.204.0.0/14, 148.216.0.0/14, 148.201.0.0/16
NetName
LACNIC-ERX-148-201-0-0
NetHandle
NET-148-201-0-0-1
Parent
NET148 (NET-148-0-0-0-0)
NetType
Transferred to LACNIC
Organization
Latin American and Caribbean IP address Regional Registry (LACNIC)
RegDate
2003-10-29
Updated
2023-04-27
Ref
https://rdap.arin.net/registry/ip/148.201.0.0
OrgName
Latin American and Caribbean IP address Regional Registry
OrgId
LACNIC
Address
Rambla Republica de Mexico 6125
City
Montevideo
PostalCode
11400
Country
UY
OrgAbuseHandle
LWI100-ARIN
OrgAbuseName
LACNIC Whois Info
OrgAbusePhone
+598-2604-2222
OrgAbuseEmail
abuse@lacnic.net
OrgAbuseRef
https://rdap.arin.net/registry/entity/LWI100-ARIN
OrgTechHandle
LACNIC-ARIN
OrgTechName
LACNIC Whois Info
OrgTechPhone
+598-2604-2222
Attack Logs
| Date | Target Location | Protocol | Link |
|---|---|---|---|
| 2026-08-17 | Digitaloceantoronto Combined | Multiple | View Log |
Disclaimer
This page contains threat intelligence information for the IPv4 address 148.204.110.113 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.