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>
This pull request introduces a new CodeQL query for detecting prompt injection vulnerabilities in Python code targeting AI prompting APIs such as agents and openai. The changes includes a new experimental query, new taint flow and type models, a customizable dataflow configuration, documentation, and comprehensive test coverage.
This PR adds a query to detect a Cross Origin Resource Sharing(CORS) policy bypass due to an incorrect check.
This PR attempts to detect the vulnerability pattern found in CVE-2022-3457
```python
if request.method in ['POST', 'PUT', 'PATCH', 'DELETE']:
origin = request.headers.get('Origin', None)
if origin and not origin.startswith(request.base):
raise cherrypy.HTTPError(403, 'Unexpected Origin header')
```
In this case, a value obtained from a header is compared using `startswith` call. This comparision is easily bypassed resulting in a CORS bypass. Given that similar bugs have been found in other languages as well, I think this PR would be a great addition to the exisitng python query pack.
The databases for CVE-2022-3457 can be downloaded from
```
https://filetransfer.io/data-package/i4Mfepls#linkhttps://file.io/V67T4SSgmExF
```
Js2Py is a Javascript to Python translation library written in Python. It allows users to invoke JavaScript code directly from Python.
The Js2Py interpreter by default exposes the entire standard library to it's users. This can lead to security issues if a malicious input were directly.
This PR includes a CodeQL query along with a qhelp and testcases to detect cases where an untrusted input flows to an Js2Py eval call.
This query successfully detects CVE-2023-0297 in `pyload/pyload`along with it's fix.
The databases can be downloaded from the links bellow.
```
https://file.io/qrMEjSJJoTq1https://filetransfer.io/data-package/a02eab7V#link
```
