I was listening to a talk from Stefan Simenon on their CI/CD transformation within ABN AMRO, a large financial company. One of the interesting things he noted was that they consider open source to be less secure, possibly with more vulnerabilities than in house written software. Their build pipeline will fail if a developer starts using new OSS components.

I find that interesting, as the DORA 2018 State of DevOps report sees more use of OSS software in companies that are adopting DevOps. In general, I think that having many people able to view the source and find errors makes companies feel that open source is more secure. I think that's likely more true, though it's a bit of a philosophical argument. We can look at some data, but it's hard to prove that one or the other is empirically more secure.

The thing I agree with is that using new components without some review is not a good idea. Whether this is written in-house, copied from an Open Source project, or purchased from a vendor, we need to perform some testing and analysis of the code or component.

This is also true in database code. When we get a query from a developer, it's often easy to determine what is happening, but when the size of code grows, or there is a large stored procedure, we often don't perform a detailed analysis. What's worse, we don't have good static code analysis tools for database languages. As much as I like what Redgate Software has done with SQL Prompt, I know this is rudimentary and is built to avoid code smells. There isn't any detailed look at whether the code is secure, or if there might be unintended effects.

There aren't really any good tools I've seen, though I'm not even sure what I'd want here. How can a tool tell me that querying 4 tables and updating 3 more is OK, but an insert to some other table in a separate database is bad. That insert to the other database might be what a malicious actor wants to copy data elsewhere. The best thing to me would be some analysis of what objects are being touched and how, which could help alert developers to potential issues.

Building static code analysis tools for database languages is hard, but it's something that our industry needs to do. This is even more true when we start to have more programmability features, like the ability to execute other languages inside of our database engines. In those cases, not only do we need to ensure the code for another language passes test, but that we understand what types of interactions our database code has with those modules.

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