Flips the Python dataflow trunk from the legacy CFG (semmle/python/Flow.qll)
and legacy ESSA SSA (semmle/python/essa/*) to the new shared CFG facade
(semmle.python.controlflow.internal.Cfg) and the new SSA adapter
(semmle.python.dataflow.new.internal.SsaImpl), both introduced
additively in the preceding PRs in this stack.
This is the trunk-flip equivalent of the original draft PR #21894 (kept
around as documentation), rebased on top of the four preparatory PRs:
P1: Remove AstNode.getAFlowNode() and rewrite callers (#21919).
P2: Qualify Flow.qll's AST references with Py:: prefix (#21920).
P3: Add new shared-CFG-backed control flow graph (#21921).
P4: Add new shared-SSA-backed SSA adapter (#21923).
The Python dataflow library (semmle/python/dataflow/new/) now imports
the new CFG facade and SSA adapter. All CFG-typed predicates
(ControlFlowNode, CallNode, BasicBlock, NameNode, AttrNode, ...) are
qualified with the Cfg:: prefix; SSA references switch from
EssaVariable/EssaDefinition to SsaImpl::Definition/SourceVariable.
GuardNode is redesigned to use the new CFG's outcome-node model
(isAfterTrue / isAfterFalse) instead of the legacy ConditionBlock +
flipped indirection. Only BarrierGuard<...> is preserved as public
API.
Framework files (Bottle, FastApi, Django, Tornado, Pyramid, Stdlib,
...) are updated to take CFG nodes from the new facade.
A handful of dataflow consistency tweaks for the new CFG:
- Augmented-assignment targets are treated as both load and store.
- 'from X import *' produces uncertain SSA writes for unknown names.
- CFG nodes are canonicalised so dataflow does not see equivalent
pre/post-order pairs as distinct nodes.
Two AST tweaks for the new CFG:
- AstNodeImpl: omit PEP 695 type-parameter names from
FunctionDefExpr / ClassDefExpr children.
- ImportResolution: drop the legacy essa import.
Test churn (~175 files): reblessed library- and query-test .expected
files reflect slightly different CFG granularity, different toString
output, and a handful of true alert deltas in security queries.
Verification: all 367 lib + src + consistency-queries compile clean.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
- remove `tupleStoreStep` and `dictStoreStep` from `containerStep`
These are imprecise compared to the content being precise.
- add implicit reads to recover taint at sinks
- add implicit read steps for decoders
to supplement the `AdditionalTaintStep`
that now only covers when the full container is tainted.
This commit removes SSA nodes from the data flow graph. Specifically, for a definition and use such as
```python
x = expr
y = x + 2
```
we used to have flow from `expr` to an SSA variable representing x and from that SSA variable to the use of `x` in the definition of `y`. Now we instead have flow from `expr` to the control flow node for `x` at line 1 and from there to the control flow node for `x` at line 2.
Specific changes:
- `EssaNode` from the data flow layer no longer exists.
- Several glue steps between `EssaNode`s and `CfgNode`s have been deleted.
- Entry nodes are now admitted as `CfgNodes` in the data flow layer (they were filtered out before).
- Entry nodes now have a new `toString` taking into account that the module name may be ambigous.
- Some tests have been rewritten to accomodate the changes, but only `python/ql/test/experimental/dataflow/basic/maximalFlowsConfig.qll` should have semantic changes.
- Comments have been updated
- Test output has been updated, but apart from `python/ql/test/experimental/dataflow/basic/maximalFlows.expected` only `python/ql/test/experimental/dataflow/typetracking-summaries/summaries.py` should have a semantic change. This is a bonus fix, probably meaning that something was never connected up correctly.
turn "the long jump" that would end up
straight at the argument into a short jump
that ends up at the dictionary being written to.
Dataflow takes care of the rest of the path.
Query operators that interpret JavaScript
are no longer considered sinks.
Instead they are considered decodings
and the output is the tainted dictionary.
The state changes to `DictInput` to reflect
that the user now controls a dangerous dictionary.
This fixes the spurious result and moves the error reporting
to a more logical place.
This allows us to make more precise modelling
The query tests now pass.
I do wonder, if there is a cleaner approach, similar to
`TaintedObject` in JavaScript. I want the option to
get this query in the hands of the custumors before
such an investigation, though.
