156.245.93.232 Threat Intelligence and Host Information

General

IP Address
156.245.93.232
IPv4 Address
Location
🇭🇰 Hong Kong
HK
Network
AS134548
DXTL Tseung Kwan O Service
Threat Score
10/100
Low Risk
Geographic Location
Country
Hong Kong
City
Unknown
Region
Unknown
Coordinates
22.2578, 114.1657
Network Information
ASN
AS134548
Organization
DXTL Tseung Kwan O Service
Network
AS134548 DXTL Tseung Kwan O Service
WHOIS Information
NetRange
156.245.0.0 - 156.245.255.255
CIDR
156.245.0.0/16
NetName
AFRINIC-ERX-156-245-0-0
NetHandle
NET-156-245-0-0-1
Parent
NET156 (NET-156-0-0-0-0)
NetType
Transferred to AfriNIC
OriginAS
Organization
African Network Information Center (AFRINIC)
RegDate
2004-05-17
Updated
2015-05-04
Comment
The African & Indian Ocean Internet Registry
Ref
https://rdap.arin.net/registry/entity/AFRINIC
OrgName
African Network Information Center
OrgId
AFRINIC
Address
Lot 19, Cybercity
City
Ebene
StateProv
PostalCode
Country
MU
OrgTechHandle
GENER11-ARIN
OrgTechName
Generic POC
OrgTechPhone
+230 4666616
OrgTechEmail
abusepoc@afrinic.net
OrgTechRef
https://rdap.arin.net/registry/entity/GENER11-ARIN

  • Country: Hong Kong
  • Network: AS134548 dxtl tseung kwan o service
  • Noticed: 1 times
  • Protcols Attacked: SSH
  • Passive DNS Results: jiaodianzhifu.com slitter-sheeterru.com marciolessa.com grafiknotlari.com haihedianlan.com zqgxbjp.com

Malware Detected on Host

Count: 3 29ea6d13be70c98e1da7fb48996b8fdf09bce35020aeb0480fdcec0aad6f938c b0e35f9a994e883493c7f0c07108c73415cb77a0696ff93e624b0d4b789ca27f 5405c586e8914b7071336fca581d31b94b5a5be5c2331c63d27dc26b3fc217a8

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Disclaimer
This page contains threat intelligence information for the IPv4 address 156.245.93.232 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.