170.84.134.172 Threat Intelligence - Nicaragua | IP Address Lookup
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General
IP Address
170.84.134.172
Location
🇳🇮 Managua, Nicaragua
Network
AS263765
Threat Score
37/100
Attack Intelligence
MITRE ATT&CK Techniques
T1110 - Brute Force
Noticed
7 times
Protocols Attacked
combined portscan telnet
Open Ports Detected
2380
Geographic Location
Country
Nicaragua
City
Managua
Region
Managua Department
Coordinates
12.1346, -86.2469
Network Information
ASN
AS263765
Organization
XINWEI INTELCOM.NIC, S.A.
Network
AS263765 XINWEI INTELCOM.NIC, S.A.
WHOIS Information
NetRange
170.84.0.0 - 170.84.227.255
CIDR
170.84.224.0/22, 170.84.128.0/18, 170.84.192.0/19, 170.84.0.0/17
NetName
LACNIC-ERX-170-84-0-0
NetHandle
NET-170-84-0-0-1
Parent
NET170 (NET-170-0-0-0-0)
NetType
Transferred to LACNIC
Organization
Latin American and Caribbean IP address Regional Registry (LACNIC)
RegDate
2010-11-03
Updated
2022-03-15
Comment
This IP address range is under LACNIC responsibility
Ref
https://rdap.arin.net/registry/ip/170.84.0.0
OrgName
Latin American and Caribbean IP address Regional Registry
OrgId
LACNIC
Address
Rambla Republica de Mexico 6125
City
Montevideo
PostalCode
11400
Country
UY
OrgTechHandle
LACNIC-ARIN
OrgTechName
LACNIC Whois Info
OrgTechPhone
+598-2604-2222
OrgTechRef
https://rdap.arin.net/registry/entity/LACNIC-ARIN
OrgAbuseHandle
LWI100-ARIN
OrgAbuseName
LACNIC Whois Info
OrgAbusePhone
+598-2604-2222
Attack Logs
| Date | Target Location | Protocol | Link |
|---|---|---|---|
| 2026-09-05 | Toronto, Canada | TELNET | View Log |
| 2026-09-05 | Digitaloceantoronto Combined | Multiple | View Log |
Disclaimer
This page contains threat intelligence information for the IPv4 address 170.84.134.172 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.