spamscanner VS SpamAssassin

Same problem as well; there are so many attack vectors it's absurd.

I've tried rspamd, SpamAssassin, and so many other alternatives. Then I decided to try writing my own in JS.

Spam Scanner (work in progress) is at https://spamscanner.net with source code at https://github.com/spamscanner. Trying to do it in a privacy-focused way, which is incredibly challenging to say the least.

Fortunately we're thinking that with ARF in combination with human curators (privacy-focused where sensitive data is redacted during curation process), and a combination of tech - will make this at least a bit better - and completely open source too.

We're in the progress of building an SMTP alternative, so we're not just a forwarding service (Forward Email at https://forwardemail.net) - and I hope to have Spam Scanner hooked in to individual inboxes as well, so it gets smarter for the individual users as opposed to group-think.

I'm hoping that we can at least make things a bit smarter with some scrappy measures over time. Hoping to launch SMTP by April so you can use Thunderbird, Apple Mail, or K-9 for instance with your own inbox running Spam Scanner.

For a detailed description of these fields, refer to the docs. Typically, the result in the is_spam field should be enough to give you confidence that your email will not be marked as spam. Note that spamscanner does not assign a numerical value but instead opts to return a boolean.

spamassassin or rspamd or ASSP. All very good. Spamassassin just works, but you need to feed it a good cohort of spam and ham (about 1000 messages each). Most people only send it the spam which will then bias it quite a bit and not have it classify spam as spam unless it's the worst of the bunch. Spamassassin is a filter for your mail server. rspamd is the same idea. ASSP is highly configurable and a proxy.

https://spamassassin.apache.org/ ?

I'm currently looking into using a Bayesian spam filter like Bogofilter or Apache Spamassassin to help out. I'd run the contents of my Contact Us form through the filter after the initial validation, and if the contents are below my spam threshold, I would actually send out the contact us request.

Avoid it. Apache's SpameAssassin flags several TLDs including .xyz as 'suspicious' nTLD[1].

[1]: https://github.com/apache/spamassassin/blob/trunk/rulesrc/sa...

The famous spam filter SpamAssassin. Score: -0.6. A score below -5 is considered spam. -0.1 DKIM_SIGNED Message has a DKIM or DK signature, not necessarily valid This rule is automatically applied if your email contains a DKIM signature but other positive rules will also be added if your DKIM signature is valid. See immediately below. 0.1 DKIM_VALID Message has at least one valid DKIM or DK signature Great! Your signature is valid 0.1 DKIM_VALID_AU Message has a valid DKIM or DK signature from author's domain Great! Your signature is valid and it's coming from your domain name 0.1 DKIM_VALID_EF Message has a valid DKIM or DK signature from envelope-from domain -0.001 HTML_MESSAGE HTML included in message No worry, that's expected if you send HTML emails 0.001 RCVD_IN_MSPIKE_H2 Average reputation (+2) 23.83.209.151 listed in wl.mailspike.net -0.001 SPF_HELO_NONE SPF: HELO does not publish an SPF Record 0.001 SPF_PASS SPF: sender matches SPF record Great! Your SPF is valid -0.01 T_KAM_HTML_FONT_INVALID Test for Invalidly Named or Formatted Colors in HTML -0.644 URIBL_SBL Contains an URL listed in the SBL blocklist -0.1 URIBL_SBL_A Contains URL\'s A record listed in the SBL blocklist

Maybe you updated spamassassin in the process? Because it looks like they have a list of "spammy TLDs" and .site is in it.

To detect whether incoming emails are malicious, mail servers also use spam scanners, such as Apache's popular SpamAssasin. The internal workings of these spam scanners can be somewhat complicated (involving Naive Bayes Classifiers on trained, large datasets, for the curious), but the primary takeaway is that these classification systems typically assign a numerical point value to an incoming email to determine the validity of the message. The higher the score, the more likely that the email is spam. For reference, the ISP Optimum states the following regarding their spam filtering: