These very small dependencies that are then later causing issues either due to malicious nature or incompetence, have become pervasive in computing (for some reason). I think that these should be less of an issue now than ever. Outside of the largest, most critical dependencies, you really shouldn't be pulling in small libraries anymore. Just generate the code via AI. AI is not great at large scale programming I think, but its amazing at snippets of code. Something I ran into recently, I needed to use FFT2 on some matrices, and what I was using didn't have an existing solution. Converting some numpy fft2 tests to my target language, and having a full native implementation of fft2, and an accompanying test suite so it will behave exactly like numpy fft2. A few minutes and a few thousand lines of code later, I have a trusted implementation. Saves me an external dependency, some weird glue code, and an attack vector.