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 •
CVSS: 5.5EPSS: 0%CPEs: 5EXPL: 0CVE-2021-41218 – Integer division by 0 in `tf.raw_ops.AllToAll`
https://notcve.org/view.php?id=CVE-2021-41218
TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `AllToAll` can be made to execute a division by 0. This occurs whenever the `split_count` argument is 0. 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/a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9crf-c6qr-r273 • CWE-369: Divide By Zero •
CVSS: 7.8EPSS: 0%CPEs: 5EXPL: 0CVE-2021-41206 – Incomplete validation of shapes in multiple TF ops
https://notcve.org/view.php?id=CVE-2021-41206
TensorFlow is an open source platform for machine learning. In affected versions several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or `CHECK`-fail related crashes but in some scenarios writes and reads from heap populated arrays are also possible. We have discovered these issues internally via tooling while working on improving/testing GPU op determinism. As such, we don't have reproducers and there will be multiple fixes for these issues. • https://github.com/tensorflow/tensorflow/commit/4d74d8a00b07441cba090a02e0dd9ed385145bf4 https://github.com/tensorflow/tensorflow/commit/4dddb2fd0b01cdd196101afbba6518658a2c9e07 https://github.com/tensorflow/tensorflow/commit/579261dcd446385831fe4f7457d802a59685121d https://github.com/tensorflow/tensorflow/commit/68422b215e618df5ad375bcdc6d2052e9fd3080a https://github.com/tensorflow/tensorflow/commit/da4aad5946be30e5f049920fa076e1f7ef021261 https://github.com/tensorflow/tensorflow/commit/e7f497570abb6b4ae5af4970620cd880e4c0c904 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p • CWE-354: Improper Validation of Integrity Check Value •
CVSS: 8.8EPSS: 0%CPEs: 5EXPL: 0CVE-2021-41208 – Incomplete validation in boosted trees code
https://notcve.org/view.php?id=CVE-2021-41208
TensorFlow is an open source platform for machine learning. In affected versions the code for boosted trees in TensorFlow is still missing validation. As a result, attackers can trigger denial of service (via dereferencing `nullptr`s or via `CHECK`-failures) as well as abuse undefined behavior (binding references to `nullptr`s). An attacker can also read and write from heap buffers, depending on the API that gets used and the arguments that are passed to the call. Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. • https://github.com/tensorflow/tensorflow/commit/5c8c9a8bfe750f9743d0c859bae112060b216f5c https://github.com/tensorflow/tensorflow/security/advisories/GHSA-57wx-m983-2f88 • CWE-476: NULL Pointer Dereference CWE-824: Access of Uninitialized Pointer •