The new CFG previously only emitted exception edges for explicit `raise`
and `assert` statements. As a result, code that became reachable only
via the exception path of an arbitrary expression (e.g., the body of an
`except` handler following a try-body whose `call()` could raise) was
classified as dead, breaking analyses like StackTraceExposure,
FileNotAlwaysClosed, ExceptionInfo, UseOfExit, and CatchingBaseException.
This commit adds a `mayThrow` predicate over expressions that are known
sources of implicit exceptions in Python (calls, attribute access,
subscripts, arithmetic/comparison operators, imports, await/yield/yield
from) plus `from m import *` at the statement level, and routes them
through the shared CFG's `beginAbruptCompletion(_, _, ExceptionSuccessor,
always=false)` hook.
The set of exception sources is restricted to nodes that are
syntactically inside a `try`/`with` statement in the same scope.
This mirrors Java's `ControlFlowGraph::mayThrow`, which only emits
exception edges where local handling can observe them — outside such
contexts, the edges add CFG complexity (weakening BarrierGuard
precision and breaking SSA continuity around augmented assignments and
subscript stores) without analysis benefit, since exceptions just
propagate to the function exit anyway.
Net effect on the test suite: ~100 alerts restored across the exception-
related query tests (StackTraceExposure +29, ExceptionInfo +17,
FileNotAlwaysClosed +52, UseOfExit +1, CatchingBaseException restored)
with no precision regressions. Affected `.expected` files and the
regression-guard `dead_under_no_raise.py` are updated accordingly.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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>
We now find an alert on this line as we hope to
It is not an alert for _full_ SSRF, though, since that configuration cannot handle multiple substitutions.
- 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.
Looking at the results of the the previous DCA run, there was a bunch of
false positives where `bind` was being used with a `AF_UNIX` socket (a
filesystem path encoded as a string), not a `(host, port)` tuple. These
results should be excluded from the query, as they are not vulnerable.
Ideally, we would just add `.TupleElement[0]` to the MaD sink, except we
don't actually support this in Python MaD...
So, instead I opted for a more low-tech solution: check that the
argument in question flows from a tuple in the local scope.
This eliminates a bunch of false positives on `python/cpython` leaving
behind four true positive results.
This takes care of most of the false negatives from the preceding
commit.
Additionally, we add models for some known wrappers of `socket.socket`
from the `gevent` and `eventlet` packages.
Adds test cases from github/codeql#21582 demonstrating false negatives:
- Address stored in class attribute (`self.bind_addr`)
- `os.environ.get` with insecure default value
- `gevent.socket` (alternative socket module)
