multiple
rbl Check
[NOTE: See our 'Judging a DNSBL' guide further down this page]
Visitors are welcome to see if their IP or domain name is blacklisted by invaluement on our invaluement lookup & removal request form. However, if you are NOT here for a removal request and, instead, you just want to discover which lists are blacklisting some IPs (not domains), then why not do your research on a web site that checks the IPs against multiple spam blacklists, including the invaluement lists?
If that is your intention, then please try out the following web sites which allow you the check sending IPs against a variety of commonly used DNSBLs, including the invaluement lists:
Also, if you operate a DNSBL lookup site and you want to add ivmSIP and ivmSIP/24 to your lookup form, please contact us and we'll help you implement that feature on your lookup site... and then we will add your site to the list above.
Judging a DNSBL
1. does use of that spam blacklist help your filtering to be
more efficient? (for example, cases where a spam is blocked by the
invaluement lists which might have been caught anyways, but would have
required much more CPU/memory/time to catch it had the invaluement lists
not been in use). A common example of this is where larger amounts of
spam are blocked by ivmSIP up front, even if a portion of those would
have been blocked by later content filtering. Such efficiency gains
means that your current hardware and software will "scale" better and
this can translate to fewer hardware and software purchases in the future!
2. Is there less spam making it into real user's inboxes ("real users"
instead of just running this against honeypot traps) For example, when compared to
the total volume of incoming spam, the invaluement lists often don't block that much
extra spam. But since the invaluement lists block much spam missed by
other lists, this tiny percent of incoming spam can actually be a rather
large percentage of all the spam that your current filter misses. For
example, suppose your current filter blocks 98.5% of all spam... and use
of the invaluement lists pushes this to 99.0% of all spam blocked. That
0.5% gain doesn't sound like much. But the user sees 1.5% spam missed go
down to 1.0% spam missed. This means 33% less spam in the users'
inboxes (as an example stat). That is a huge gain!
RECAP: For this reason, don't judge a list based on hit/miss checking. Instead, implement that list in your filtering as a test, and see what it hits on that your filtering would have otherwise missed. It may only hit on a few hundred spams out of hundreds of thousands. That ratio means that hand-testing would make such a list seem unworthy. But if those hundreds of spams would have otherwise hit your user’s mailboxes without use of that spam blacklist, then such a list is very valuable. For this reason, hand checking can be very limited and misleading in comparision to employing the list in your spam filtering. (Therefore, those interested in testing out the invaluement lists should read the instructions here for a free test! Do NOT try to judge the invaluement lists by just a few hand-submitted items checked. You’ll miss out if you only do that much.)
3. Are the False Positives extremely rare? If they are not, then all
of the above points are diminished. But if FPs really are extremely
rare, and the other points above hold up, then use of the invaluement
DNSBLs will lead to a positive step forward for your spam filtering.
4. If all of the above prove true, then a final extra benefit might be
providing the "leeway" to back off of the scoring (just a tad) of some
very effective spam filtering methods which have, in the past, proven
necessary for blocking many prolific series of spams, but which,
unfortunately, cause just a tiny bit too high FPs. For example, recently
we found that too many legitimate e-mails had their sending IP
blacklisted in two particular famous DNSBLs. We already were using both of those RBLs for
scoring instead of outright blocking. But the combination of the two
scores was triggering occasional egregious FPs in our own spam filtering
for our e-mail hosting clients (though NOT in the invaluement DNSBL
data!). At the same time, we made some other improvements to our spam
filtering which then gave us the ability to lower both of those RBL scores by a seemingly small, but actually very
critical, 1 point. With those other improvements, we were able to do
this without causing missed spams (FNs). In the same way, adding another high quality DNSBL might also give you the room to back off on the
scoring for some other lists, or filtering methods, which cause
occasional FPs.
multiple
rbl check
