CVSS: 5.5EPSS: 0%CPEs: 5EXPL: 1CVE-2021-41222 – Segfault due to negative splits in `SplitV`
https://notcve.org/view.php?id=CVE-2021-41222
TensorFlow is an open source platform for machine learning. In affected versions the implementation of `SplitV` can trigger a segfault is an attacker supplies negative arguments. This occurs whenever `size_splits` contains more than one value and at least one value is negative. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. • https://github.com/tensorflow/tensorflow/commit/25d622ffc432acc736b14ca3904177579e733cc6 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cpf4-wx82-gxp6 • CWE-682: Incorrect Calculation •
CVSS: 7.8EPSS: 0%CPEs: 5EXPL: 1CVE-2021-41228 – Code injection in `saved_model_cli`
https://notcve.org/view.php?id=CVE-2021-41228
TensorFlow is an open source platform for machine learning. In affected versions TensorFlow's `saved_model_cli` tool is vulnerable to a code injection as it calls `eval` on user supplied strings. This can be used by attackers to run arbitrary code on the plaform where the CLI tool runs. However, given that the tool is always run manually, the impact of this is not severe. We have patched this by adding a `safe` flag which defaults to `True` and an explicit warning for users. • https://github.com/tensorflow/tensorflow/commit/8b202f08d52e8206af2bdb2112a62fafbc546ec7 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3rcw-9p9x-582v • CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection') CWE-94: Improper Control of Generation of Code ('Code Injection') •
CVSS: 7.8EPSS: 0%CPEs: 5EXPL: 1CVE-2021-41221 – Access to invalid memory during shape inference in `Cudnn*` ops
https://notcve.org/view.php?id=CVE-2021-41221
TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for the `Cudnn*` operations in TensorFlow can be tricked into accessing invalid memory, via a heap buffer overflow. This occurs because the ranks of the `input`, `input_h` and `input_c` parameters are not validated, but code assumes they have certain values. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. • https://github.com/tensorflow/tensorflow/commit/af5fcebb37c8b5d71c237f4e59c6477015c78ce6 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cqv6-3phm-hcwx • CWE-120: Buffer Copy without Checking Size of Input ('Classic Buffer Overflow') CWE-787: Out-of-bounds Write •
CVSS: 7.8EPSS: 0%CPEs: 5EXPL: 0CVE-2021-41216 – Heap buffer overflow in `Transpose`
https://notcve.org/view.php?id=CVE-2021-41216
TensorFlow is an open source platform for machine learning. In affected versions the shape inference function for `Transpose` is vulnerable to a heap buffer overflow. This occurs whenever `perm` contains negative elements. The shape inference function does not validate that the indices in `perm` are all valid. The fix will be included in TensorFlow 2.7.0. • https://github.com/tensorflow/tensorflow/commit/c79ba87153ee343401dbe9d1954d7f79e521eb14 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3ff2-r28g-w7h9 • CWE-120: Buffer Copy without Checking Size of Input ('Classic Buffer Overflow') CWE-787: Out-of-bounds Write •
CVSS: 5.5EPSS: 0%CPEs: 5EXPL: 0CVE-2021-41213 – Deadlock in mutually recursive `tf.function` objects
https://notcve.org/view.php?id=CVE-2021-41213
TensorFlow is an open source platform for machine learning. In affected versions the code behind `tf.function` API can be made to deadlock when two `tf.function` decorated Python functions are mutually recursive. This occurs due to using a non-reentrant `Lock` Python object. Loading any model which contains mutually recursive functions is vulnerable. An attacker can cause denial of service by causing users to load such models and calling a recursive `tf.function`, although this is not a frequent scenario. • https://github.com/tensorflow/tensorflow/commit/afac8158d43691661ad083f6dd9e56f327c1dcb7 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h67m-xg8f-fxcf • CWE-662: Improper Synchronization CWE-667: Improper Locking •