This was causing issues with imports with many "dots" in the name.
Previously, the test added in this commit would not have the desired
result for the `check` call.
This was due to bad manual magic: restricting the attribute name makes
sense when we're talking about submodules of a package, but it doesn't
when we're talking about reexported modules.
Also (hopefully) fixes the tests so that the Python 3-specific bits are
ignored under Python 2.
Extends the tests to
1. Account parts of the test code that may be specific to Python 2 or 3,
2. Also track which arguments passed to `check` are references to
modules.
The latter revealed a bunch of spurious results, which I have annotated
accordingly.
I could have sworn I added all of them to the batch, but somehow these slipped through.
Co-authored-by: yoff <lerchedahl@gmail.com>
Co-authored-by: Rasmus Wriedt Larsen <rasmuswriedtlarsen@gmail.com>
I ported the predicates showing difference between points-to and
type-tracking, since it's helpful to see the list of differences,
instead of having to parse expectations!
I don't see the value from this, so just going to outright delete it.
(it actually stayed alive for quite some time in the original git history,
but never seemed to be that useful.)
The selected edges is covered by `NormalDataflowTest.ql` now... and
reading the test-output changes in `edges` is just going to make commits
larger while not providing any real value.
A slightly complicated test setup. I wanted to both make sure I captured
the semantics of Python and also the fact that the kinds of global flow
we expect to see are indeed present.
The code is executable, and prints out both when the execution reaches
certain files, and also what values are assigned to the various
attributes that are referenced throughout the program. These values are
validated in the test as well.
My original version used introspection to avoid referencing attributes
directly (thus enabling better error diagnostics), but unfortunately
that made it so that the model couldn't follow what was going on.
The current setup is a bit clunky (and Python's scoping rules makes it
especially so -- cf. the explicit calls to `globals` and `locals`), but
I think it does the job okay.
I realized the modeling was done in a non-recommended way, so I changed
the modeling. It was very nice that I could use API graphs for the flask
part, and a little sad when I couldn't for Django/Tornado.
It's really hard to audit that this is all good.. I tried my best with
`icdiff` though -- and there is a problem with
ql/src/experimental/Security/CWE-348/ClientSuppliedIpUsedInSecurityCheck.ql
that needs to be fixed in the next commit
The other callables return control flow nodes,
so it is slightly inconsistent for this to return a
data flow node, but it does make models based
on API graphs nicer.
