41.208.191.234 Threat Intelligence - Senegal | IP Address Lookup
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General
IP Address
41.208.191.234
Location
πΈπ³ Dakar, Senegal
Network
AS8346
Threat Score
5/100
Attack Intelligence
Protocols Attacked
fake mitre
Geographic Location
Country
Senegal
City
Dakar
Region
Dakar
Coordinates
14.6935, -17.4480
Network Information
ASN
AS8346
Organization
IDDQD-AS
Network
AS8346 IDDQD-AS
WHOIS Information
inetnum
41.208.128.0 - 41.208.191.255
netname
SN-SONATEL-20060614
descr
Societe Nationale Des Telecommunications Du Senegal
country
SN
org
ORG-SNDT1-AFRINIC
admin-c
SBT7-AFRINIC
tech-c
SBT7-AFRINIC
status
ALLOCATED PA
mnt-by
AFRINIC-HM-MNT
mnt-lower
SMM-MNT
mnt-domains
SMM-MNT
parent
41.0.0.0 - 41.255.255.255
organisation
ORG-SNDT1-AFRINIC
org-name
SONATEL Societe Nationale Des Telecommunications Du Senegal
org-type
LIR
address
Societe Nationale Des Telecommunications Du Senegal
phone
tel:+221-33-879-32-22
mnt-ref
AFRINIC-HM-MNT
person
Alpha Mbodj
nic-hdl
AM2490-AFRINIC
fax-no
tel:+221-8392236
route
41.208.128.0/18
origin
AS8346
Attack Logs
| Date | Target Location | Protocol | Link |
|---|---|---|---|
| 2026-10-24 | Webexploit Mitre T1593 Ip List 2026 10 24 | Multiple | View Log |
| 2026-10-24 | Webexploit Fake Googlebot Ip List 2026 10 24 | Multiple | View Log |
| 2026-10-21 | Webexploit Mitre T1593 Ip List 2026 10 21 | Multiple | View Log |
| 2026-10-21 | Webexploit Fake Googlebot Ip List 2026 10 21 | Multiple | View Log |
| 2026-07-14 | Webexploit Fake Googlebot Ip List 2026 07 14 | Multiple | View Log |
| 2026-07-14 | Webexploit Mitre T1593 Ip List 2026 07 14 | Multiple | View Log |
Disclaimer
This page contains threat intelligence information for the IPv4 address 41.208.191.234 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.