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fortigate firewall monitor
#1
Hello,

Please is there anyone who is monitoring fortigate firewall with snmp trap can help me?

Thanks 
hbib
 Reply
#2
I modified the pandora server.conf  "snmp_console 1" , then I went to the snmp generator
, at the end the result is: 
[img]data:image/png;base64,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[/img]
how can I check the correct result or nn?


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#3
Hello,

The first data in the table (the red box in the screenshot) indicates the status of the trap received, if it is red it means that it has not been validated, I am not clear if this is what you mean by "correct result". In any case I leave below the link to the documentation of the section you mention, I hope it will be helpful.

Greetings
Diego
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