How does the spam watcher in Freshdesk work?

The spam watcher will check if more than 50 emails have been received from the same email address in the first 30 minutes; if so, upon the 51st email, the user will be deleted and all emails from them will be sent to the spam folder.

After the 60th minute, if emails are still being received from that email address, the spam watcher will block that ID and Freshdesk will not receive any further emails from them.

By leveraging a variety of techniques and filters, we effectively prevent spam and unwanted messages from reaching your helpdesk. It's essential to note that our methods and features may have evolved since then. However, here are some common techniques we employ:

• Bayesian Filtering: We use Bayesian filtering, which is a statistical approach. It learns from previous spam patterns and user feedback to categorize incoming emails as spam or non-spam. As it processes more emails, it becomes better at identifying spam.
• CAPTCHA: To prevent automated bots from submitting spam tickets, we have CAPTCHA challenges that require users to prove their humanity by solving visual puzzles or answering questions.
• Email Verification: When customers create new tickets via email, we send an email verification link to confirm the legitimacy of their email address. This ensures that only genuine email addresses can submit tickets.
• Blacklist and Whitelist: You have control over a blacklist to block specific email addresses or domains known for sending spam. Additionally, you can create a whitelist of trusted sources to ensure important emails aren't marked as spam.
• Ticket Filter Rules using automation: You can set up custom ticket filter rules/automation to automatically handle incoming tickets based on specific criteria. These rules help identify potential spam tickets for appropriate handling.
• Spam Notifications: We flag incoming tickets that appear to be spam and notify agents, so they can review and take necessary actions.
• Machine Learning: We leverage machine learning algorithms to analyze various ticket attributes and identify patterns consistent with spam or legitimate queries.

Please remember that spam filtering is an ongoing process, and we continuously improve our filters to keep up with evolving spam tactics.