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CVSS: 5.5EPSS: 0%CPEs: 6EXPL: 0

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.SparseReshape` can be made to trigger an integral division by 0 exception. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/reshape_util.cc#L176-L181) calls the reshaping functor whenever there is at least an index in the input but does not check that shape of the input or the target shape have both a non-zero number of elements. The [reshape functor](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/reshape_util.cc#L40-L78) blindly divides by the dimensions of the target shape. Hence, if this is not checked, code will result in a division by 0. • https://github.com/tensorflow/tensorflow/commit/4923de56ec94fff7770df259ab7f2288a74feb41 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-95xm-g58g-3p88 • CWE-369: Divide By Zero •

CVSS: 5.5EPSS: 0%CPEs: 6EXPL: 0

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.SparseDenseCwiseDiv` is vulnerable to a division by 0 error. The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc#L56) uses a common class for all binary operations but fails to treat the division by 0 case separately. We have patched the issue in GitHub commit d9204be9f49520cdaaeb2541d1dc5187b23f31d9. The fix will be included in TensorFlow 2.6.0. • https://github.com/tensorflow/tensorflow/commit/d9204be9f49520cdaaeb2541d1dc5187b23f31d9 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hp4c-x6r7-6555 • CWE-369: Divide By Zero •

CVSS: 9.1EPSS: 0%CPEs: 1EXPL: 2

TensorFlow through 2.5.0 allows attackers to overwrite arbitrary files via a crafted archive when tf.keras.utils.get_file is used with extract=True. NOTE: the vendor's position is that tf.keras.utils.get_file is not intended for untrusted archives ** EN DISPUTA ** TensorFlow versiones hasta 2.5.0, permite a atacantes sobrescribir archivos arbitrarios por medio de un archivo diseñado cuando se usa la función tf.keras.utils.get_file con extract=True. NOTA: la posición del proveedor es que la función tf.keras.utils.get_file no está pensado para archivos no confiables • https://github.com/miguelc49/CVE-2021-35958-2 https://github.com/miguelc49/CVE-2021-35958-1 https://docs.python.org/3/library/tarfile.html#tarfile.TarFile.extractall https://github.com/tensorflow/tensorflow/blob/b8cad4c631096a34461ff8a07840d5f4d123ce32/tensorflow/python/keras/README.md https://github.com/tensorflow/tensorflow/blob/b8cad4c631096a34461ff8a07840d5f4d123ce32/tensorflow/python/keras/utils/data_utils.py#L137 https://keras.io/api https://vuln.ryotak.me/advisories/52 • CWE-22: Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal') •

CVSS: 7.8EPSS: 0%CPEs: 4EXPL: 1

TensorFlow is an end-to-end open source platform for machine learning. Calling TF operations with tensors of non-numeric types when the operations expect numeric tensors result in null pointer dereferences. The conversion from Python array to C++ array(https://github.com/tensorflow/tensorflow/blob/ff70c47a396ef1e3cb73c90513da4f5cb71bebba/tensorflow/python/lib/core/ndarray_tensor.cc#L113-L169) is vulnerable to a type confusion. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. • https://github.com/tensorflow/tensorflow/commit/030af767d357d1b4088c4a25c72cb3906abac489 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-452g-f7fp-9jf7 • CWE-476: NULL Pointer Dereference CWE-843: Access of Resource Using Incompatible Type ('Type Confusion') •

CVSS: 7.8EPSS: 0%CPEs: 2EXPL: 1

TensorFlow is an end-to-end open source platform for machine learning. If the `splits` argument of `RaggedBincount` does not specify a valid `SparseTensor`(https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor), then an attacker can trigger a heap buffer overflow. This will cause a read from outside the bounds of the `splits` tensor buffer in the implementation of the `RaggedBincount` op(https://github.com/tensorflow/tensorflow/blob/8b677d79167799f71c42fd3fa074476e0295413a/tensorflow/core/kernels/bincount_op.cc#L430-L446). Before the `for` loop, `batch_idx` is set to 0. The attacker sets `splits(0)` to be 7, hence the `while` loop does not execute and `batch_idx` remains 0. • https://github.com/tensorflow/tensorflow/commit/eebb96c2830d48597d055d247c0e9aebaea94cd5 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8h46-5m9h-7553 • CWE-787: Out-of-bounds Write •