Last week, I ran AINAScan — our AI-powered static analysis tool — against FlaskBlog, a popular open-source Flask project. It found two security issues back-to-back. Here's the breakdown.
The bigger finding was a classic IDOR (Insecure Direct Object Reference) vulnerability. A user could directly reference another user's resource by ID without any authorization check. This is issue #254.
The second finding — issue #258 — is subtler. In , the search results query fetches the full user row including the field, and that tuple gets passed directly into the template context:
The template currently only renders and . So no hash is displayed right now. But the data is there — one accidental in the template (during a future edit) would expose bcrypt hashes to every visitor.
Most developers don't think twice about or selecting all columns for convenience. But every field you expose to the template layer is a surface area that can leak — through:
Principle of Least Privilege applies to data too. Only pass what the template actually needs.
AINAScan traces data flow from the query result tuple through to the template render call. It flags cases where sensitive field names (like , , ) appear in a query but the result is passed to a render function without explicit field filtering.
No execution needed — pure static AST + data flow analysis.
The maintainer acknowledged the finding and is bundling the fix with the IDOR patch in v3. Closing as duplicate of #254.
Before every call, ask: do I actually need all these fields? If your ORM returns a model object or a raw tuple with 10+ columns, consider projecting down to only what the view needs.
AINAScan is open-source and free to try. Drop your repo URL and see what it finds: github.com/moonsehwan/aina-scan Do you explicitly filter query results before passing to templates, or do you SELECT * and let the template decide what to show?