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Switches the trunk dataflow library and all in-tree consumers
(frameworks, ApiGraphs, Concepts, regexp, security customisations,
test harness) from the legacy Flow.qll/ESSA stack to the new
shared-CFG facade (Cfg.qll) and the ESSA-shaped adapter on the
shared-SSA library (SsaImpl.qll).
Highlights:
* DataFlowPublic/Private/Dispatch, Attributes, VariableCapture,
IterableUnpacking, ImportResolution, ImportStar, LocalSources,
TaintTrackingPrivate, MatchUnpacking, TypeTrackingImpl,
SsaImpl, Builtins all now qualify CFG/SSA references with
Cfg:: / SsaImpl:: and stop pulling in semmle.python.essa.*.
* AstNodeImpl.qll/Cfg.qll: ImportMember exposes its inner
ImportExpr, DefinitionNode.getValue covers Alias / AnnAssign /
AugAssign / AssignExpr / For-target / Parameter-default,
ForNode is treated as an expression node, AnnotatedExitNode is
canonical, and BoolExprNode.getAnOperand drops the dominance
constraint that did not hold for short-circuit BBs.
* SsaImpl.qll: parameters always get a ParameterDefinition (so
unused parameters still have SSA defs), scope-entry defs for
module globals require an actual store somewhere, scope-exit
has a synthetic use so reaching-defs survives to module
boundary, and the legacy SsaSourceVariable / EssaVariable
surface (getName, getScope, getAUse, getASourceUse,
getAnImplicitUse) is reinstated for downstream queries.
* DataFlowPublic.qll: GuardNode redesigned around the new
structural outcome nodes (isAfterTrue / isAfterFalse). The
legacy ConditionBlock + flipped indirection is gone;
controlsBlock walks UP through 'not' / '==True' / 'is False'
etc. via outcomeOfGuard, accumulating polarity cleanly. Only
BarrierGuard<...> is preserved as public API.
* ModuleVariableNode.getAWrite and LocalFlow::definitionFlowStep
bypass SSA and consult Cfg::NameNode.defines /
Cfg::DefinitionNode.getValue directly, so that write defs
pruned by shared SSA (because the variable has no in-scope
read) still produce dataflow steps.
* Frameworks + downstream consumers: replace
EssaVariable.hasDefiningNode, getAReturnValueFlowNode,
Parameter.getDefault, Scope.getEntryNode / getANormalExit etc.
with CFG-side bridges through Cfg::ControlFlowNode.
The legacy Flow.qll / Essa.qll stack is untouched and remains
available for queries that import it directly.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
113 lines
4.3 KiB
Plaintext
113 lines
4.3 KiB
Plaintext
/**
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* Provides classes modeling security-relevant aspects of the `pydantic` PyPI package.
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*
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* See
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* - https://pypi.org/project/pydantic/
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* - https://pydantic-docs.helpmanual.io/
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*/
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private import python
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private import semmle.python.controlflow.internal.Cfg as Cfg
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private import semmle.python.dataflow.new.DataFlow
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private import semmle.python.dataflow.new.TaintTracking
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private import semmle.python.Concepts
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private import semmle.python.ApiGraphs
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private import semmle.python.frameworks.data.ModelsAsData
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/**
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* INTERNAL: Do not use.
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*
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* Provides models for `pydantic` PyPI package.
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*
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* See
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* - https://pypi.org/project/pydantic/
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* - https://pydantic-docs.helpmanual.io/
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*/
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module Pydantic {
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/**
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* Provides models for `pydantic.BaseModel` subclasses (a pydantic model).
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*
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* See https://pydantic-docs.helpmanual.io/usage/models/.
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*/
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module BaseModel {
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/** Gets a reference to a `pydantic.BaseModel` subclass (a pydantic model). */
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API::Node subclassRef() {
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result = API::moduleImport("pydantic").getMember("BaseModel").getASubclass+()
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or
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result = ModelOutput::getATypeNode("pydantic.BaseModel~Subclass").getASubclass*()
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}
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/**
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* A source of instances of `pydantic.BaseModel` subclasses, extend this class to model new instances.
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*
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* This can include instantiations of the class, return values from function
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* calls, or a special parameter that will be set when functions are called by an external
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* library.
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*
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* Use the predicate `BaseModel::instance()` to get references to instances of `pydantic.BaseModel`.
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*/
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abstract class InstanceSource extends DataFlow::LocalSourceNode { }
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/** Gets a reference to an instance of a `pydantic.BaseModel` subclass. */
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private DataFlow::TypeTrackingNode instance(DataFlow::TypeTracker t) {
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t.start() and
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result instanceof InstanceSource
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or
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t.start() and
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instanceStepToPydanticModel(_, result)
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or
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exists(DataFlow::TypeTracker t2 | result = instance(t2).track(t2, t))
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}
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/** Gets a reference to an instance of a `pydantic.BaseModel` subclass. */
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DataFlow::Node instance() { instance(DataFlow::TypeTracker::end()).flowsTo(result) }
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/**
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* A step from an instance of a `pydantic.BaseModel` subclass, that might result in
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* an instance of a `pydantic.BaseModel` subclass.
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*
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* NOTE: We currently overapproximate, and treat all attributes as containing
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* another pydantic model. For the code below, we _could_ limit this to `main_foo`
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* and members of `other_foos`. IF THIS IS CHANGED, YOU MUST CHANGE THE ADDITIONAL
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* TAINT STEPS BELOW, SUCH THAT SIMPLE ACCESS OF SOMETHING LIKE `str` IS STILL
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* TAINTED.
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*
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*
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* ```py
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* class MyComplexModel(BaseModel):
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* field: str
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* main_foo: Foo
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* other_foos: List[Foo]
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* ```
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*/
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private predicate instanceStepToPydanticModel(DataFlow::Node nodeFrom, DataFlow::Node nodeTo) {
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// attributes (such as `model.foo`)
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nodeFrom = instance() and
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nodeTo.(DataFlow::AttrRead).getObject() = nodeFrom
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or
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// subscripts on attributes (such as `model.foo[0]`). This needs to handle nested
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// lists (such as `model.foo[0][0]`), and access being split into multiple
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// statements (such as `xs = model.foo; xs[0]`).
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//
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// To handle this we overapproximate which things are a Pydantic model, by
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// treating any subscript on anything that originates on a Pydantic model to also
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// be a Pydantic model. So `model[0]` will be an overapproximation, but should not
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// really cause problems (since we don't expect real code to contain such accesses)
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nodeFrom = instance() and
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nodeTo.asCfgNode().(Cfg::SubscriptNode).getObject() = nodeFrom.asCfgNode()
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}
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/**
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* Extra taint propagation for `pydantic.BaseModel` subclasses. (note that these could also be `pydantic.BaseModel` subclasses)
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*/
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private class AdditionalTaintStep extends TaintTracking::AdditionalTaintStep {
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override predicate step(DataFlow::Node nodeFrom, DataFlow::Node nodeTo) {
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// NOTE: if `instanceStepToPydanticModel` is changed to be more precise, these
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// taint steps should be expanded, such that a field that has type `str` is
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// still tainted.
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instanceStepToPydanticModel(nodeFrom, nodeTo)
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}
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}
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}
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}
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