[Rspamd-Users] Email hits BAYES_* after a few times
Sophie Loewenthal
sophie at klunky.co.uk
Sun Jun 2 20:39:35 UTC 2019
> On 2 Jun 2019, at 22:33, Sophie Loewenthal <sophie at klunky.co.uk> wrote:
>
>
>> On 2 Jun 2019, at 22:17, Tim Harman via Users <users at lists.rspamd.com> wrote:
>>
>> On 03/06/2019 6:47 am, Sophie Loewenthal wrote:
>>> Hi,
>>> For some reason emails that come in more than twice start hitting
>>> BAYES_* rule, but these emails were not processed by 'rspamc
>>> learn_spam' or 'rspamc learn_ham', those can be discounted. How does
>>> this email get into BAYES when I didn’t feed any eamils from the
>>> sender into rspamc learn_spam?
>>
>> <snip>
>>
>>> It’s a bit rum : How could i investigate this?
>>> Thank, Sophie
>>
>> What does "rspamadm configdump classifier" tell you?
>> Probably you have autolearn enabled, thus rspamd is automatically learning your ham/spam.
>>
>> Suggested Reading: https://rspamd.com/doc/configuration/statistic.html
>
>
> Hi Tim,
>
> I thought autolearn was disabled, unless it’s on by default. I don’t have autolearn = true in my config that I know of. Bayes should be autolearning and configdump didn’t shed any light.
>
>
> # rspamadm configdump classifier
> *** Section classifier ***
> bayes {
> backend = "sqlite3";
> min_tokens = 11;
> languages_enabled = true;
> cache {
> path = "/var/lib/rspamd/learn_cache.sqlite";
> }
> statfile {
> path = "/var/lib/rspamd/bayes.ham.sqlite";
> spam = false;
> symbol = "BAYES_HAM";
> }
> statfile {
> path = "/var/lib/rspamd/bayes.spam.sqlite";
> spam = true;
> symbol = "BAYES_SPAM";
> }
> tokenizer {
> name = "osb";
> }
> learn_condition = <<EOD
> return function(task, is_spam, is_unlearn)
> local learn_type = task:get_request_header('Learn-Type')
>
> if not (learn_type and tostring(learn_type) == 'bulk') then
> local prob = task:get_mempool():get_variable('bayes_prob', 'double')
>
> if prob then
> local in_class = false
> local cl
> if is_spam then
> cl = 'spam'
> in_class = prob >= 0.95
> else
> cl = 'ham'
> in_class = prob <= 0.05
> end
>
> if in_class then
> return false,string.format('already in class %s; probability %.2f%%',
> cl, math.abs((prob - 0.5) * 200.0))
> end
> end
> end
>
> return true
> end
> EOD;
> min_learns = 200;
> }
>
> *** End of section classifier ***
Big type above:
> Bayes should *not* be autolearning and configdump didn’t shed any light.
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