CVE-2020-15204

In eager mode, TensorFlow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1 does not set the session state. Hence, calling tf.rawops.GetSessionHandle or tf.rawops.GetSessionHandleV2 results in a null pointer dereference In linked snippet, in eager mode, ctx-sessionstate returns nullptr. Since...

CVE-2020-15204 Segfault in Tensorflow

In eager mode, TensorFlow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1 does not set the session state. Hence, calling tf.rawops.GetSessionHandle or tf.rawops.GetSessionHandleV2 results in a null pointer dereference In linked snippet, in eager mode, ctx-sessionstate returns nullptr. Since...

CVE-2020-15205

CVE-2020-15205 affects TensorFlow: the data_splits parameter of tf.raw_ops.StringNGrams lacks validation, allowing crafted input that can cause heap overflow and memory leakage, potentially leaking memory contents and aiding ASLR defeat. Affected TF versions include 1.15.4 and 2.x releases up to ...

CVE-2020-15205

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the datasplits argument of tf.rawops.StringNGrams lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory In the linked code snippet, all the binary strings after ...

CVE-2020-15205 Data leak in Tensorflow

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the datasplits argument of tf.rawops.StringNGrams lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory In the linked code snippet, all the binary strings after ...

CVE-2020-15206

CVE-2020-15206 affects TensorFlow: changing SavedModel protocol buffers and required key names can cause segfaults and data corruption while loading models, leading to a denial of service in inference deployments. The vulnerability was addressed with fixes committed in TF, and TensorFlow versions...

CVE-2020-15206 Denial of Service in Tensorflow

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, changing the TensorFlow's SavedModel protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using tensorflow-servin...

CVE-2020-15206

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, changing the TensorFlow's SavedModel protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using tensorflow-servin...

CVE-2020-15207

CVE-2020-15207 affects TensorFlow Lite: negative indexing support uses ResolveAxis and only debug builds validate the converted index, allowing out-of-bounds access that can cause segfaults/data corruption. Affected: TensorFlow Lite before 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1. Root cause: insuffici...

CVE-2020-15207

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, to mimic Python's indexing with negative values, TFLite uses ResolveAxis to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds. If the...

CVE-2020-15207 Segfault and data corruption in tensorflow-lite

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, to mimic Python's indexing with negative values, TFLite uses ResolveAxis to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds. If the...

CVE-2020-15208

The CVE-2020-15208 issue affects TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1. A debug-only DCHECK used to determine the common tensor dimension returns the first tensor’s size, which can be larger than the second tensor’s, allowing reads/writes outside bounds. This is a...

CVE-2020-15208

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a DCHECK which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can...

CVE-2020-15208 Data corruption in tensorflow-lite

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a DCHECK which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can...

CVE-2020-15209

Observation: CVE-2020-15209 affects TensorFlow Lite. A crafted TFLite flatbuffer can flip a tensor’s buffer index, turning a read-only tensor into read-write, which the runtime may treat as writable and initialize with a null buffer, causing a null pointer dereference. The issue has a concrete ro...

CVE-2020-15209 Null pointer dereference in tensorflow-lite

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, a crafted TFLite model can force a node to have as input a tensor backed by a nullptr buffer. This can be achieved by changing a buffer index in the flatbuffer serialization to convert a read-only tensor to a read-write one...

CVE-2020-15210 Segmentation fault in tensorflow-lite

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b a...

CVE-2020-15210

CVE-2020-15210 affects TensorFlow/TFLite where a saved model reuses the same tensor as input and output for an operator, causing a segmentation fault or memory corruption depending on the operator. The issue has a patch in commit d58c96946b2880991d63d1dacacb32f0a4dfa453 and is addressed in patch ...

CVE-2020-15211 Out of bounds access in tensorflow-lite

In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indice...

CVE-2020-15211

CVE-2020-15211 : In TensorFlow Lite (before 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1), a negative -1 tensor index used for optional inputs can be treated as a valid index during validation, allowing out-of-bounds reads/writes in some operators. The root cause is the double indexing scheme for tensors i...