Kushalkhemka/embedding-cve-nvd-dataset huggingface dataset:
nsorflow/core/kernels/ragged_tensor_to_variant_op.cc#L129) has an incomplete validation of the splits values, missing the case when the argument would be empty. We have patched the issue in GitHub commit be7a4de6adfbd303ce08be4332554dff70362612. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w4xf-2pqw-5mq7 - https://github.com/tensorflow/tensorflow/commit/be7a4de6adfbd303ce08be4332554dff70362612
CVE ID: CVE-2021-37667 State: PUBLISHED Published: 2021-08-12T21:40:10 Last Updated: 2024-08-04T01:23:01.485Z Severity: HIGH (CVSS 7.8 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-824 Description: TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.UnicodeEncode`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/unicode_ops.cc#L533-L539) reads the first dimension of the `input_splits` tensor before validating that th
/core/kernels/unicode_ops.cc#L533-L539) reads the first dimension of the `input_splits` tensor before validating that this tensor is not empty. We have patched the issue in GitHub commit 2e0ee46f1a47675152d3d865797a18358881d7a6. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w74j-v8xh-3w5h - https://github.com/tensorflow/tensorflow/commit/2e0ee46f1a47675152d3d865797a18358881d7a6
CVE ID: CVE-2021-37668 State: PUBLISHED Published: 2021-08-12T22:30:12 Last Updated: 2024-08-04T01:23:01.519Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-369 Description: TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause denial of service in applications serving models using `tf.raw_ops.UnravelIndex` by triggering a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/unravel_index_op.cc#L36) does not check that the tensor subsumed by `dims` is not
161b1964f15f4/tensorflow/core/kernels/unravel_index_op.cc#L36) does not check that the tensor subsumed by `dims` is not empty. Hence, if one element of `dims` is 0, the implementation does a division by 0. We have patched the issue in GitHub commit a776040a5e7ebf76eeb7eb923bf1ae417dd4d233. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2wmv-37vq-52g5 - https://github.com/tensorflow/tensorflow/commit/a776040a5e7eb
rflow/tensorflow/security/advisories/GHSA-2wmv-37vq-52g5 - https://github.com/tensorflow/tensorflow/commit/a776040a5e7ebf76eeb7eb923bf1ae417dd4d233
CVE ID: CVE-2021-37669 State: PUBLISHED Published: 2021-08-12T22:55:17 Last Updated: 2024-08-04T01:23:01.462Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-681 Description: TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause denial of service in applications serving models using `tf.raw_ops.NonMaxSuppressionV5` by triggering a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/image/non_max_suppression_op.cc#L170-L271) uses a user controlled argument
b61a16d161b1964f15f4/tensorflow/core/kernels/image/non_max_suppression_op.cc#L170-L271) uses a user controlled argument to resize a `std::vector`. However, as `std::vector::resize` takes the size argument as a `size_t` and `output_size` is an `int`, there is an implicit conversion to unsigned. If the attacker supplies a negative value, this conversion results in a crash. A similar issue occurs in `CombinedNonMaxSuppression`. We have patched the issue in GitHub commit 3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d and commit [b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFl
be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vmjw-c2vp-p33c - https://github.com/tensorflow/tensorflow/commit/3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d - https://github.com/tensorflow/tensorflow/commit/b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58
CVE ID: CVE-2021-37670 State: PUBLISHED Published: 2021-08-12T22:25:16 Last Updated: 2024-08-04T01:23:01.507Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N) Vendors: tensorflow Products: tensorflow Problem Types: CWE-125 Description: TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.UpperBound`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/searchsorted_op.cc#L85-L104) does not validate the rank of `sorted_input`
0b61a16d161b1964f15f4/tensorflow/core/kernels/searchsorted_op.cc#L85-L104) does not validate the rank of `sorted_input` argument. A similar issue occurs in `tf.raw_ops.LowerBound`. We have patched the issue in GitHub commit 42459e4273c2e47a3232cc16c4f4fff3b3a35c38. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9697-98pf-4rw7 - https://github.com/tensorflow/tensorflow/commit/42459e4273c2e47a3232cc16c4f4fff3b3a35c
/advisories/GHSA-9697-98pf-4rw7 - https://github.com/tensorflow/tensorflow/commit/42459e4273c2e47a3232cc16c4f4fff3b3a35c38
CVE ID: CVE-2021-37671 State: PUBLISHED Published: 2021-08-12T21:40:22 Last Updated: 2024-08-04T01:23:01.520Z Severity: HIGH (CVSS 7.8 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-824 Description: TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.Map*` and `tf.raw_ops.OrderedMap*` operations. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L222-L248) has a check in place to ensure that `indices` is
b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L222-L248) has a check in place to ensure that `indices` is in ascending order, but does not check that `indices` is not empty. We have patched the issue in GitHub commit 532f5c5a547126c634fefd43bbad1dc6417678ac. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qr82-2c78-4m8h - https://github.com/tensorflow/tensorflow/commit/532f5c5a547126c634fefd43bbad1d
security/advisories/GHSA-qr82-2c78-4m8h - https://github.com/tensorflow/tensorflow/commit/532f5c5a547126c634fefd43bbad1dc6417678ac
CVE ID: CVE-2021-37672 State: PUBLISHED Published: 2021-08-12T22:20:11 Last Updated: 2024-08-04T01:23:01.434Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N) Vendors: tensorflow Products: tensorflow Problem Types: CWE-125 Description: TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.SdcaOptimizerV2`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/sdca_internal.cc#L320-L353) does not check that the length of `exampl
78fb00b61a16d161b1964f15f4/tensorflow/core/kernels/sdca_internal.cc#L320-L353) does not check that the length of `example_labels` is the same as the number of examples. We have patched the issue in GitHub commit a4e138660270e7599793fa438cd7b2fc2ce215a6. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5hj3-vjjf-f5m7 - https://github.com/tensorflow/tensorflow/commit/a4e138660270e7599793fa438cd7b2fc2ce215a6
CVE ID: CVE-2021-37673 State: PUBLISHED Published: 2021-08-12T22:55:11 Last Updated: 2024-08-04T01:23:01.441Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-20 Description: TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.MapStage`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L513) does not check that the `key` input is a valid non-empty tensor. We have patched the issue in GitHub commi
e_op.cc#L513) does not check that the `key` input is a valid non-empty tensor. We have patched the issue in GitHub commit d7de67733925de196ec8863a33445b73f9562d1d. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-278g-rq84-9hmg - https://github.com/tensorflow/tensorflow/commit/d7de67733925de196ec8863a33445b73f9562d1d
CVE ID: CVE-2021-37674 State: PUBLISHED Published: 2021-08-12T22:40:19 Last Updated: 2024-08-04T01:23:01.520Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-20 Description: TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a denial of service via a segmentation fault in `tf.raw_ops.MaxPoolGrad` caused by missing validation. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/maxpooling_op.cc) misses some validation for the `orig_input` and `orig_output` tensors. T
f15f4/tensorflow/core/kernels/maxpooling_op.cc) misses some validation for the `orig_input` and `orig_output` tensors. The fixes for CVE-2021-29579 were incomplete. We have patched the issue in GitHub commit 136b51f10903e044308cf77117c0ed9871350475. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7ghq-fvr3-pj2x - https://github.com/tensorflow/tensorflow/commit/136b51f10903e044308cf77117c0ed9871350475 - https://git
-7ghq-fvr3-pj2x - https://github.com/tensorflow/tensorflow/commit/136b51f10903e044308cf77117c0ed9871350475 - https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-068.md
CVE ID: CVE-2021-37675 State: PUBLISHED Published: 2021-08-12T21:45:11 Last Updated: 2024-08-04T01:23:01.430Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-369 Description: TensorFlow is an end-to-end open source platform for machine learning. In affected versions most implementations of convolution operators in TensorFlow are affected by a division by 0 vulnerability where an attacker can trigger a denial of service via a crash. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/framework/common_shape_fns.cc#L577) is
sorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/framework/common_shape_fns.cc#L577) is missing several validations before doing divisions and modulo operations. We have patched the issue in GitHub commit 8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c8h-2mv3-49ww - https://github.com/tensorflow/tensorflow/commit/8a793b5d7f59e37ac7f3cd095
flow/security/advisories/GHSA-9c8h-2mv3-49ww - https://github.com/tensorflow/tensorflow/commit/8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4
CVE ID: CVE-2021-37676 State: PUBLISHED Published: 2021-08-12T21:40:27 Last Updated: 2024-08-04T01:23:01.528Z Severity: HIGH (CVSS 7.8 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-824 Description: TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.SparseFillEmptyRows`. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/sparse_ops.cc#L608-L634) does not validate that the input arguments are not empty tensor
1b1964f15f4/tensorflow/core/ops/sparse_ops.cc#L608-L634) does not validate that the input arguments are not empty tensors. We have patched the issue in GitHub commit 578e634b4f1c1c684d4b4294f9e5281b2133b3ed. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v768-w7m9-2vmm - https://github.com/tensorflow/tensorflow/commit/578e634b4f1c1c684d4b4294f9e5281b2133b3ed
CVE ID: CVE-2021-37677 State: PUBLISHED Published: 2021-08-12T22:35:10 Last Updated: 2024-08-04T01:23:01.450Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-20 Description: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axi
sorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References
, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qfpc-5pjr-mh26 - https://github.com/tensorflow/tensorflow/commit/da857cfa0fde8f79ad0afdbc94e88b5d4bbec764
CVE ID: CVE-2021-37678 State: PUBLISHED Published: 2021-08-12T23:05:10 Last Updated: 2024-08-04T01:23:01.401Z Severity: CRITICAL (CVSS 9.3 CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-502 Description: TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/python/keras/saving/model_config.py#L66-L104) uses `yaml.unsafe_load` which can perform arbitrary code e
15f4/tensorflow/python/keras/saving/model_config.py#L66-L104) uses `yaml.unsafe_load` which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r6jx-9g48-2r5r - https://github.com/tensorf
erences: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r6jx-9g48-2r5r - https://github.com/tensorflow/tensorflow/commit/23d6383eb6c14084a8fc3bdf164043b974818012
CVE ID: CVE-2021-37679 State: PUBLISHED Published: 2021-08-12T22:20:16 Last Updated: 2024-08-04T01:23:01.507Z Severity: HIGH (CVSS 7.1 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N) Vendors: tensorflow Products: tensorflow Problem Types: CWE-125 Description: TensorFlow is an end-to-end open source platform for machine learning. In affected versions it is possible to nest a `tf.map_fn` within another `tf.map_fn` call. However, if the input tensor is a `RaggedTensor` and there is no function signature provided, code assumes the output is a fully specified tensor and fills output buffer with uninitialized contents from the heap. The `t` and `z` outputs should be identical, however this is not th
ut buffer with uninitialized contents from the heap. The `t` and `z` outputs should be identical, however this is not the case. The last row of `t` contains data from the heap which can be used to leak other memory information. The bug lies in the conversion from a `Variant` tensor to a `RaggedTensor`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_from_variant_op.cc#L177-L190) does not check that all inner shapes match and this results in the additional dimensions. The same implementation can result in data loss, if input tensor is tweaked. We have patched the issue in GitHub commit 4e2565483d
mplementation can result in data loss, if input tensor is tweaked. We have patched the issue in GitHub commit 4e2565483d0ffcadc719bd44893fb7f609bb5f12. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g8wg-cjwc-xhhp - https://github.com/tensorflow/tensorflow/commit/4e2565483d0ffcadc719bd44893fb7f609bb5f12
CVE ID: CVE-2021-37680 State: PUBLISHED Published: 2021-08-12T21:45:17 Last Updated: 2024-08-04T01:23:01.555Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-369 Description: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of fully connected layers in TFLite is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/fully_connected.cc#L226). We have patched the issue in GitHub commit 718721986aa137691ee23f03638867151f74935f. The fix will be included in
#L226). We have patched the issue in GitHub commit 718721986aa137691ee23f03638867151f74935f. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cfpj-3q4c-jhvr - https://github.com/tensorflow/tensorflow/commit/718721986aa137691ee23f03638867151f74935f
CVE ID: CVE-2021-37681 State: PUBLISHED Published: 2021-08-12T22:00:24 Last Updated: 2024-08-04T01:23:01.508Z Severity: HIGH (CVSS 7.8 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-476 Description: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of SVDF in TFLite is [vulnerable to a null pointer error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/svdf.cc#L300-L313). The [`GetVariableInput` function](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kerne
` function](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L115-L119) can return a null pointer but `GetTensorData` assumes that the argument is always a valid tensor. Furthermore, because `GetVariableInput` calls [`GetMutableInput`](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L82-L90) which might return `nullptr`, the `tensor->is_variable` expression can also trigger a null pointer exception. We have patched the issue in GitHub commit 5b048e87e4e55990dae6b547add4dae59f4e1c76. The fix will be included in TensorFlow 2.6.0. We will als
sue in GitHub commit 5b048e87e4e55990dae6b547add4dae59f4e1c76. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7xwj-5r4v-429p - https://github.com/tensorflow/tensorflow/commit/5b048e87e4e55990dae6b547add4dae59f4e1c76