CVSS: 6.5EPSS: 0%CPEs: 6EXPL: 1CVE-2020-15210 – Segmentation fault in tensorflow-lite
https://notcve.org/view.php?id=CVE-2020-15210
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 and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. En tensorflow-lite versiones anteriores a 1.15.4, 2.0.3, 2.1.2, 2.2.1 y 2.3.1, si un modelo guardado de TFLite usa el mismo tensor como entrada y salida de un operador, entonces, dependiendo del operador, podemos observar un fallo de segmentación o solo una corrupción de la memoria. Hemos parcheado el problema en d58c96946b y publicaremos parches para todas las versiones entre 1.15 y 2.3. • http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html https://github.com/tensorflow/tensorflow/commit/d58c96946b2880991d63d1dacacb32f0a4dfa453 https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x9j7-x98r-r4w2 • CWE-20: Improper Input Validation CWE-787: Out-of-bounds Write •
CVSS: 5.8EPSS: 0%CPEs: 6EXPL: 1CVE-2020-15211 – Out of bounds access in tensorflow-lite
https://notcve.org/view.php?id=CVE-2020-15211
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 indices for the tensors, indexing into an array of tensors that is owned by the subgraph. This results in a pattern of double array indexing when trying to get the data of each tensor. However, some operators can have some tensors be optional. To handle this scenario, the flatbuffer model uses a negative `-1` value as index for these tensors. • http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html https://github.com/tensorflow/tensorflow/commit/00302787b788c5ff04cb6f62aed5a74d936e86c0 https://github.com/tensorflow/tensorflow/commit/1970c2158b1ffa416d159d03c3370b9a462aee35 https://github.com/tensorflow/tensorflow/commit/46d5b0852528ddfd614ded79bccc75589f801bd9 https://github.com/tensorflow/tensorflow/commit/cd31fd0ce0449a9e0f83dcad08d6ed7f1d6bef3f https://github.com/tensorflow/tensorflow/commit/e11f55585f614645b360563072ffeb5c3eeff162 https://github.com/tensorflow/tensorflow/commit/fff2c8326280c07733828f99054 • CWE-125: Out-of-bounds Read CWE-787: Out-of-bounds Write •
CVSS: 5.3EPSS: 0%CPEs: 3EXPL: 1CVE-2020-15191 – Undefined behavior in Tensorflow
https://notcve.org/view.php?id=CVE-2020-15191
In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes an invalid argument to `dlpack.to_dlpack` the expected validations will cause variables to bind to `nullptr` while setting a `status` variable to the error condition. However, this `status` argument is not properly checked. Hence, code following these methods will bind references to null pointers. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1. • http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8 https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q8qj-fc9q-cphr • CWE-20: Improper Input Validation CWE-252: Unchecked Return Value CWE-476: NULL Pointer Dereference •
CVSS: 4.3EPSS: 0%CPEs: 3EXPL: 1CVE-2020-15192 – Memory leak in Tensorflow
https://notcve.org/view.php?id=CVE-2020-15192
In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes a list of strings to `dlpack.to_dlpack` there is a memory leak following an expected validation failure. The issue occurs because the `status` argument during validation failures is not properly checked. Since each of the above methods can return an error status, the `status` value must be checked before continuing. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1. En Tensorflow versiones anteriores a 2.2.1 y 2.3.1, si un usuario pasa una lista de cadenas hacia "dlpack.to_dlpack", se presenta una pérdida de memoria después de un fallo de comprobación esperada. • http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8 https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8fxw-76px-3rxv • CWE-20: Improper Input Validation •
CVSS: 7.1EPSS: 0%CPEs: 3EXPL: 1CVE-2020-15193 – Memory corruption in Tensorflow
https://notcve.org/view.php?id=CVE-2020-15193
In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of `dlpack.to_dlpack` can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users from passing in a Python object instead of a tensor. The uninitialized memory address is due to a `reinterpret_cast` Since the `PyObject` is a Python object, not a TensorFlow Tensor, the cast to `EagerTensor` fails. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1. • http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8 https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rjjg-hgv6-h69v • CWE-908: Use of Uninitialized Resource •