I downgraded to rspamd-2.1-1, the message is no more present in log, I will report to upstream
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even if there are messages I can still leave 2.2, do you work well?
We do not use all versions, some have some eastern eggs, play as your own risk 
interesting feature with rspamd2
178466:Nov 30 11:17:36 prometheus rspamd[5999]: <c9d0bf>; proxy; rspamd_stat_check_autolearn: <DUJZO36W-23XY-3FVU-JQQF-WG8KAKDTE0GY@facilement.site>: autolearn spam for classifier 'bayes' as message's action is reject, score: 27.49
autolearn spam and ham
if score < 0 -> ham
if rejected -> spamThe module reputation (it replaces ip_score) is a good major improvement, I see it in action in logs, the score is added dynamically following several conditions
surbl has been obsoleted and replaced by rbl
Hola todos, hoy tenemos rspamd v2.2 para probar, por favor yo necessito tu ayuda
yum install nethserver-mail-server nethserver-mail-common nethserver-mail-filter --enablerepo=nethserver-testing
la QA se encuentra en github
Rspamd v2.2 is ready for the QA, please we need your tests, you can find the QA at the github page…
gracie, gracias, thank you, merci
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I am now using Libraesva antispam, so I temporarily disabled Rsapmd, 
can I still try the update even if disabled?
In the postfix configuration we set the linux socket to use rspamd, if rspamd is stopped I bet that postfix will do a soft reject (try again later)
disabling Rspamd postfix seems to work,
Nethserver receives mail from Librasva and delivers it to mailboxes, can you check if it is correct? or what should I change?
if I need it I open a new post, I wouldn’t want to go out of topic here
Yes you should open a new thread to explain what you did to switch, eventually why, it could be nice
by choice of the company management they chose Libraesva
Did some tests on my home mailserver and it looks good so far. Thanks for the great work! 
- antivirus (tested with eicar string)
- virus rejected
- clamd down, soft reject works
- clamd down, sending as authenticated user from webmail works
- reputation is there
- bayes filter
- log entries for autolearn and bayes tokens are there
- HAM/SPAM counts up correctly
- from moving mail to junk folder
- by uploading spam/ham in rspamd UI
Not checked: Count up of ham/spam on autolearn as the mails have been learned already:
Dec 11 08:07:50 server2 rspamd[6291]: <e7d1b7>; proxy; rspamd_stat_check_autolearn: <7C7A1121.2FABD67C@cnt-grms.ec>: autolearn spam for classifier 'bayes' as message's action is reject, score: 41.70
Dec 11 08:07:50 server2 rspamd[6291]: <e7d1b7>; proxy; rspamd_task_process: learn error: <7C7A1121.2FABD67C@cnt-grms.ec> has been already learned as spam, ignore it
Dec 11 08:07:50 server2 rspamd[6291]: <e7d1b7>; lua; neural.lua:487: cannot learn ANN tRFANNACDF6FD7A287B20A260: too many spam samples: 2
I’ll report as soon as autolearn counts up.
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I installed on a production server and found a puzzling log entry. It saids 89 learned, however the dashboard says Bayes are fully trained.
I guess some rspamd internal counters are not aligned as I expect 
/cc @stephdl
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I suspect that the bayes counter has changed, where the dashboard takes its counter ?
on my server it seems relevant between what rspamc stat and what I can find in logs
/var/log/maillog-20191124:122128:Nov 24 08:16:30 prometheus rspamd[27027]: <6dd2d0>; proxy; rspamd_redis_finalize_process: cannot retreive stat tokens from Redis: skip obtaining bayes tokens for BAYES_SPAM: not enough learns 116; 200 required
/var/log/maillog-20191124:122129:Nov 24 08:16:30 prometheus rspamd[27027]: <6dd2d0>; proxy; rspamd_redis_finalize_process: cannot retreive stat tokens from Redis: skip obtaining bayes tokens for BAYES_HAM: not enough learns 57; 200 required
Once you have reached the minimal score (200) this message does not appear in log anymore
maybe I will need some logs evidence and output of rspamc stat to report to upstream
Well during the weekend the learns counter grew rapidly and reached 200.
Dec 15 00:19:12 nethservice rspamd[15843]: <5fb59c>; proxy; rspamd_redis_connected: skip obtaining bayes tokens for BAYES_SPAM of classifier bayes: not enough learns 199; 200 required
Dec 15 00:54:32 nethservice rspamd[15843]: <bc0c60>; proxy; rspamd_redis_connected: skip obtaining bayes tokens for BAYES_HAM of classifier bayes: not enough learns 199; 200 required
Then started the “skip learning” messages:
Dec 15 01:02:06 nethservice rspamd[15843]: <ebbbe5>; proxy; rspamd_task_process: skip learning: <NethServer/nethserver-httpd/pull/64/push/4397709277@github.com> is skipped for bayes classifier: already in class ham; probability 100.00%
This is the rspamc stat output:
[root@here ~]# rspamc stat
Results for command: stat (0.034 seconds)
Messages scanned: 1457081
Messages with action reject: 421653, 28.93%
Messages with action soft reject: 3528, 0.24%
Messages with action rewrite subject: 16, 0.00%
Messages with action add header: 40105, 2.75%
Messages with action greylist: 6790, 0.46%
Messages with action no action: 984989, 67.60%
Messages treated as spam: 465302, 31.93%
Messages treated as ham: 991779, 68.06%
Messages learned: 25210
Connections count: 0
Control connections count: 12
Pools allocated: 18691
Pools freed: 18658
Bytes allocated: 21.87MiB
Memory chunks allocated: 128
Shared chunks allocated: 17
Chunks freed: 0
Oversized chunks: 1547
Fuzzy hashes in storage "local": 0
Fuzzy hashes in storage "rspamd.com": 905848192
Fuzzy hashes stored: 905848192
Statfile: BAYES_SPAM type: redis; length: 0; free blocks: 0; total blocks: 0; free: 0.00%; learned: 3261; users: 39; languages: 0
Statfile: BAYES_HAM type: redis; length: 0; free blocks: 0; total blocks: 0; free: 0.00%; learned: 11001; users: 1251; languages: 0
Total learns: 14262
The Total learns counter here is really big. And the one used by the Dashboard UI, Messages learned is even bigger:
curl --connect-timeout 2 'http://localhost:11334/auth'
{
"version": "2.2",
"auth": "ok",
"uptime": 248605,
"clean": 985008,
"probable": 40121,
"greylist": 6790,
"reject": 421653,
"soft_reject": 3528,
"scanned": 1457100,
"learned": 25210,
"read_only": false,
"config_id": "token"
}
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I report upstream why we have all counters with different numbers
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I tested also the behavior if ClamAV is not responding. All seems fine and ready for a production release!
Edit: update to rspamd 2.2 released.
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