This text is the primary in a sequence of posts I am writing about working varied SaaS merchandise and web sites for the final 8 years. I will be sharing a few of the points I’ve handled, classes I’ve realized, errors I’ve made, and perhaps just a few issues that went proper. Let me know what you suppose!
Again in 2019 or 2020, I had determined to rewrite the whole backend for Block Sender, a SaaS utility that helps customers create higher e mail blocks, amongst different options. Within the course of, I added just a few new options and upgraded to rather more trendy applied sciences. I ran the exams, deployed the code, manually examined all the things in manufacturing, and aside from just a few random odds and ends, all the things gave the impression to be working nice. I want this was the top of the story, however…
Just a few weeks later, I used to be notified by a buyer (which is embarrassing in itself) that the service wasn’t working and so they had been getting numerous should-be-blocked emails of their inbox, so I investigated. Many occasions this subject is because of Google eradicating the connection from our service to the consumer’s account, which the system handles by notifying the consumer by way of e mail and asking them to reconnect, however this time it was one thing else.
It seemed just like the backend employee that handles checking emails in opposition to consumer blocks stored crashing each 5-10 minutes. The weirdest half – there have been no errors within the logs, reminiscence was high-quality, however the CPU would sometimes spike at seemingly random occasions. So for the subsequent 24 hours (with a 3-hour break to sleep – sorry prospects 😬), I needed to manually restart the employee each time it crashed. For some cause, the Elastic Beanstalk service was ready far too lengthy to restart, which is why I needed to do it manually.
Debugging points in manufacturing is at all times a ache, particularly since I could not reproduce the difficulty domestically, not to mention determine what was responsible for it. So like every “good” developer, I simply began logging all the things and waited for the server to crash once more. For the reason that CPU was spiking periodically, I figured it wasn’t a macro subject (like once you run out of reminiscence) and was in all probability being brought on by a particular e mail or consumer. So I attempted to slim it down:
- Was it crashing on a sure e mail ID or kind?
- Was it crashing for a given buyer?
- Was it crashing at some common interval?
After hours of this, and gazing logs longer than I might care to, finally, I did slim it all the way down to a particular buyer. From there, the search house narrowed fairly a bit – it was more than likely a blocking rule or a particular e mail our server stored retrying on. Fortunately for me, it was the previous, which is a far simpler downside to debug provided that we’re a really privacy-focused firm and do not retailer or view any e mail knowledge.
Earlier than we get into the precise downside, let’s first speak about one in every of Block Sender’s options. On the time I had many shoppers asking for wildcard blocking, which might permit them to dam sure kinds of e mail addresses that adopted the identical sample. For instance, if you happen to wished to dam all emails from advertising and marketing e mail addresses, you might use the wildcard advertising and marketing@* and it might block all emails from any handle that began with advertising and marketing@.
One factor I did not take into consideration is that not everybody understands how wildcards work. I assumed that most individuals would use them in the identical means I do as a developer, utilizing one * to signify any variety of characters. Sadly, this specific consumer had assumed you wanted to make use of one wildcard for every character you wished to match. Of their case, they wished to dam all emails from a sure area (which is a local characteristic Block Sender has, however they have to not have realized it, which is an entire downside in itself). So as a substitute of utilizing *@instance.com, they used **********@instance.com.
POV: Watching your customers use your app…
To deal with wildcards on our employee server, we’re utilizing the Node.js library matcher, which helps with glob matching by turning it into a daily expression. This library would then flip **********@instance.com into one thing like the next regex:
/[sS]*[sS]*[sS]*[sS]*[sS]*[sS]*[sS]*[sS]*[sS]*[sS]*@instance.com/i
When you’ve got any expertise with regex, you recognize that they will get very sophisticated in a short time, particularly on a computational degree. Matching the above expression to any cheap size of textual content turns into very computationally costly, which ended up tying up the CPU on our employee server. That is why the server would crash each jiffy; it might get caught attempting to match a posh common expression to an e mail handle. So each time this consumer acquired an e mail, along with all the retries we in-built to deal with short-term failures, it might crash our server.
So how did I repair this? Clearly, the fast repair was to seek out all blocks with a number of wildcards in succession and proper them. However I additionally wanted to do a greater job of sanitizing consumer enter. Any consumer may enter a regex and take down the whole system with a ReDoS assault.
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Dealing with this specific case was pretty easy – take away successive wildcard characters:
block = block.change(/*+/g, '*')
However that also leaves the app open to different kinds of ReDoS assaults. Fortunately there are a variety of packages/libraries to assist us with these varieties as effectively:
Utilizing a mix of the options above, and different safeguards, I have been capable of forestall this from taking place once more. Nevertheless it was a superb reminder that you could by no means belief consumer enter, and you need to at all times sanitize it earlier than utilizing it in your utility. I wasn’t even conscious this was a possible subject till it occurred to me, so hopefully, this helps another person keep away from the identical downside.
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