Open-source AI code scanners — which one actually catches the bugs?

TLDR InfoSec pitted the biggest open-source AI code-security scanners against each other. The idea is simple: feed each tool a vulnerable repo and see which one flags the problems without drowning you in false positives. The goal is to pick a tool that actually works for the average dev, not just for a research paper.

The short answer is that no single scanner wins across the board. Some are fast but miss things. Others are precise but slow enough to be annoying in CI. A few are built for one language or one framework and fall apart the moment you step outside their lane. The real takeaway is that the tooling is still settling — you'll likely run two or three of them in parallel and let them cross-check each other.

If you're shipping code for a living, the practical move is to pick one as your default, add a second for a different angle, and set up a daily run that emails you only the new findings. Don't try to automate the whole thing yet; the false-positive rates are still too high to trust without a human glance. The landscape will keep shifting, so keep an eye on what the community is actually using, not what the vendors are claiming.

Why this matters for us: small teams and solo devs are the ones who get hammered by supply-chain bugs — knowing which free tools actually work keeps your code clean without adding cost or bloat.