Headline
CVE-2022-36016: Strengthen input verification for SpecializeType by replacing DCHECK … · tensorflow/tensorflow@6104f0d
TensorFlow is an open source platform for machine learning. When tensorflow::full_type::SubstituteFromAttrs receives a FullTypeDef& t that is not exactly three args, it triggers a CHECK-fail instead of returning a status. We have patched the issue in GitHub commit 6104f0d4091c260ce9352f9155f7e9b725eab012. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
@@ -510,6 +510,19 @@ TEST(SpecializeType, ForEachOverridesTargetOfNestedForEach) {
EXPECT_EQ(t_actual.args(1).args(0).args(0).args_size(), 0);
}
TEST(SpecializeType, ForEachRejectsMalformedInput) {
OpDef op;
FullTypeDef* t = op.add_output_arg()->mutable_experimental_full_type();
t->set_type_id(TFT_FOR_EACH);
t->add_args()->set_type_id(TFT_PRODUCT);
NodeDef ndef;
AttrSlice attrs(ndef);
FullTypeDef ft;
EXPECT_FALSE(SpecializeType(attrs, op, ft).ok());
}
TEST(SpecializeType, RemovesLegacyVariant) {
OpDef op;
FullTypeDef* t = op.add_output_arg()->mutable_experimental_full_type();
Related news
### Impact When [`tensorflow::full_type::SubstituteFromAttrs`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/math_ops.cc) receives a `FullTypeDef& t` that is not exactly three args, it triggers a `CHECK`-fail instead of returning a status. ```cpp Status SubstituteForEach(AttrMap& attrs, FullTypeDef& t) { DCHECK_EQ(t.args_size(), 3); const auto& cont = t.args(0); const auto& tmpl = t.args(1); const auto& t_var = t.args(2); ``` ### Patches We have patched the issue in GitHub commit [6104f0d4091c260ce9352f9155f7e9b725eab012](https://github.com/tensorflow/tensorflow/commit/6104f0d4091c260ce9352f9155f7e9b725eab012). The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more infor...