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It seems one of the major downfalls is that the user has to define all sources and sinks. I might have missed it but how do you systematically define/find these? Personally was interested in a similar topic for a thesis and stumbled upon deepcode.ai which started out of ETH Zurich (https://files.sri.inf.ethz.ch/website/papers/scalable-taint-...). Are there any plans or reasons why you would not want such a system?

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The article briefly mentions this, although it might not be super clear from the short description - "We regularly review issues reported through other avenues, such as our bug bounty program, to ensure that we correct any false negatives." We rely on these mechanisms to find places where we're missing taint coverage and write sources and sinks as necessary. As of right now, all the annotations are manual.

I hadn't looked too deeply into the literature there, the paper looks really interesting! We don't have any concrete plans to implement such a system, but I don't think there's any fundamental reason we wouldn't want automatic taint model generation. I'll give the paper a read on Monday to learn more :)

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