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Add topic modelling to freemail job scam rule #3414

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Add topic modelling to freemail job scam rule #3414

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34 changes: 22 additions & 12 deletions detection-rules/body_job_scam_freemail_pivot.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -23,18 +23,28 @@ source: |
or not any(headers.hops, any(.fields, strings.ilike(.name, "In-Reply-To")))
)
)
and 3 of (
any([subject.subject, body.current_thread.text],
regex.icontains(., '(full|part).time')
),
strings.ilike(body.current_thread.text, '*job*'),
regex.icontains(body.current_thread.text, '\bHR\b'),
strings.ilike(body.current_thread.text, '*manager*'),
strings.ilike(body.current_thread.text, '*commission*'),
strings.ilike(body.current_thread.text, '*hourly*'),
strings.ilike(body.current_thread.text, '*prior experience*'),
strings.ilike(body.current_thread.text, '*company rep*'),
strings.ilike(body.current_thread.text, "100% legal")
and (
3 of (
any([subject.subject, body.current_thread.text],
regex.icontains(., '(full|part).time')
),
strings.ilike(body.current_thread.text, '*job*'),
regex.icontains(body.current_thread.text, '\bHR\b'),
strings.ilike(body.current_thread.text, '*manager*'),
strings.ilike(body.current_thread.text, '*commission*'),
strings.ilike(body.current_thread.text, '*hourly*'),
strings.ilike(body.current_thread.text, '*per hour*'),
strings.ilike(body.current_thread.text, '*prior experience*'),
strings.ilike(body.current_thread.text, '*company rep*'),
strings.ilike(body.current_thread.text, "100% legal")
)
or (
length(ml.nlu_classifier(body.current_thread.text).topics) == 1
and any(ml.nlu_classifier(body.current_thread.text).topics,
.name == "Professional and Career Development"
and .confidence == "high"
)
)
)

// all attachments are images or there's no attachments
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