Kushalkhemka/embedding-cve-nvd-dataset huggingface dataset:
CVE ID: CVE-2021-29548 State: PUBLISHED Published: 2021-05-14T19:10:46 Last Updated: 2024-08-03T22:11:05.702Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-369 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc) does not validate all constraints specified in the op's contra
3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc) does not validate all constraints specified in the op's contract(https://www.tensorflow.org/api_docs/python/tf/raw_ops/QuantizedBatchNormWithGlobalNormalization). 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. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p45v-v4pw-77jr - https://github.com/tensorflow/tensorflow/commit/d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b
CVE ID: CVE-2021-29549 State: PUBLISHED Published: 2021-05-14T19:10:41 Last Updated: 2024-08-03T22:11:05.522Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-369 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L289-L295) computes a modulo operation without validating that the div
f151c/tensorflow/core/kernels/quantized_add_op.cc#L289-L295) computes a modulo operation without validating that the divisor is not zero. Since `vector_num_elements` is determined based on input shapes(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L522-L544), a user can trigger scenarios where this quantity is 0. 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. Additional Analyst Notes: - CVE Program Container: References: - https://github.com
fected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x83m-p7pv-ch8v - https://github.com/tensorflow/tensorflow/commit/744009c9e5cc5d0447f0dc39d055f917e1fd9e16
CVE ID: CVE-2021-29550 State: PUBLISHED Published: 2021-05-14T19:10:36 Last Updated: 2024-08-03T22:11:05.613Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-369 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.FractionalAvgPool`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L85-L89) computes a divisor quantity by dividing two user controlled values. The user co
rnels/fractional_avg_pool_op.cc#L85-L89) computes a divisor quantity by dividing two user controlled values. The user controls the values of `input_size[i]` and `pooling_ratio_[i]` (via the `value.shape()` and `pooling_ratio` arguments). If the value in `input_size[i]` is smaller than the `pooling_ratio_[i]`, then the floor operation results in `output_size[i]` being 0. The `DCHECK_GT` line is a no-op outside of debug mode, so in released versions of TF this does not trigger. Later, these computed values are used as arguments(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L96-L99) to `GeneratePoolingSeq
c8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L96-L99) to `GeneratePoolingSequence`(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_pool_common.cc#L100-L108). There, the first computation is a division in a modulo operation. Since `output_length` can be 0, this results in runtime crashing. 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. Additional Analyst Notes: - CVE Program Container: References: - https://gi
also affected and still in supported range. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f78g-q7r4-9wcv - https://github.com/tensorflow/tensorflow/commit/548b5eaf23685d86f722233d8fbc21d0a4aecb96
CVE ID: CVE-2021-29551 State: PUBLISHED Published: 2021-05-14T19:10:30 Last Updated: 2024-08-03T22:11:05.916Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-125 Description: TensorFlow is an end-to-end open source platform for machine learning. The implementation of `MatrixTriangularSolve`(https://github.com/tensorflow/tensorflow/blob/8cae746d8449c7dda5298327353d68613f16e798/tensorflow/core/kernels/linalg/matrix_triangular_solve_op_impl.h#L160-L240) fails to terminate kernel execution if one validation condition fails. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorF
validation condition fails. 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. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vqw6-72r7-fgw7 - https://github.com/tensorflow/tensorflow/commit/480641e3599775a8895254ffbc0fc45621334f68
CVE ID: CVE-2021-29552 State: PUBLISHED Published: 2021-05-14T19:10:25 Last Updated: 2024-08-03T22:11:05.801Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-617 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by controlling the values of `num_segments` tensor argument for `UnsortedSegmentJoin`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a2a607db15c7cd01d754d37e5448d72a13491bdb/tensorflow/core/kernels/unsorted_segment_join_op.cc#L92-L93) assumes that the `num_segments` tensor is a valid scalar. Si
ensorflow/core/kernels/unsorted_segment_join_op.cc#L92-L93) assumes that the `num_segments` tensor is a valid scalar. Since the tensor is empty the `CHECK` involved in `.scalar<T>()()` that checks that the number of elements is exactly 1 will be invalidated and this would result in process termination. 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. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jhq9-wm9m-cf89 - https://github.com/tensorflow/t
es: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jhq9-wm9m-cf89 - https://github.com/tensorflow/tensorflow/commit/704866eabe03a9aeda044ec91a8d0c83fc1ebdbe
CVE ID: CVE-2021-29553 State: PUBLISHED Published: 2021-05-14T19:10:20 Last Updated: 2024-08-03T22:11:05.664Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-125 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can read data outside of bounds of heap allocated buffer in `tf.raw_ops.QuantizeAndDequantizeV3`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/11ff7f80667e6490d7b5174aa6bf5e01886e770f/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L237) does not validate the value of user supplied `axis` attribute before using it to
els/quantize_and_dequantize_op.cc#L237) does not validate the value of user supplied `axis` attribute before using it to index in the array backing the `input` argument. 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. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h9px-9vqg-222h - https://github.com/tensorflow/tensorflow/commit/99085e8ff02c3763a0ec2263e44daec416f6a387
CVE ID: CVE-2021-29554 State: PUBLISHED Published: 2021-05-14T19:10:15 Last Updated: 2024-08-03T22:11:06.254Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-369 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127) computes a divisor value from user data but does not check that the result is 0 before doing the
count_ops.cc#L123-L127) computes a divisor value from user data but does not check that the result is 0 before doing the division. Since `data` is given by the `values` argument, `num_batch_elements` is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, and TensorFlow 2.3.3, as these are also affected. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qg48-85hg-mqc5 - https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f
CVE ID: CVE-2021-29555 State: PUBLISHED Published: 2021-05-14T19:17:51 Last Updated: 2024-08-03T22:11:06.286Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-369 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.FusedBatchNorm`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/828f346274841fa7505f7020e88ca36c22e557ab/tensorflow/core/kernels/fused_batch_norm_op.cc#L295-L297) performs a division based on the last dimension of the `x` tensor. Since this is controlled by
tch_norm_op.cc#L295-L297) performs a division based on the last dimension of the `x` tensor. Since this is controlled by the user, an attacker can trigger a denial of service. 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. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r35g-4525-29fq - https://github.com/tensorflow/tensorflow/commit/1a2a87229d1d61e23a39373777c056161eb4084d
CVE ID: CVE-2021-29556 State: PUBLISHED Published: 2021-05-14T19:17:46 Last Updated: 2024-08-03T22:11:06.071Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-369 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.Reverse`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/36229ea9e9451dac14a8b1f4711c435a1d84a594/tensorflow/core/kernels/reverse_op.cc#L75-L76) performs a division based on the first dimension of the tensor argument. The fix will be included in TensorFlow
75-L76) performs a division based on the first dimension of the tensor argument. 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. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fxqh-cfjm-fp93 - https://github.com/tensorflow/tensorflow/commit/4071d8e2f6c45c1955a811fee757ca2adbe462c1
CVE ID: CVE-2021-29557 State: PUBLISHED Published: 2021-05-14T19:17:41 Last Updated: 2024-08-03T22:11:06.068Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-369 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.SparseMatMul`. The division by 0 occurs deep in Eigen code because the `b` tensor is empty. 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
it 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. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xw93-v57j-fcgh - https://github.com/tensorflow/tensorflow/commit/7f283ff806b2031f407db64c4d3edcda8fb9f9f5
CVE ID: CVE-2021-29558 State: PUBLISHED Published: 2021-05-14T19:17:35 Last Updated: 2024-08-03T22:11:05.646Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-787 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `tf.raw_ops.SparseSplit`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/699bff5d961f0abfde8fa3f876e6d241681fbef8/tensorflow/core/util/sparse/sparse_tensor.h#L528-L530) accesses an array element based on a user controlled offset. The fix will be included in TensorFlow 2.5.0. We will also c
ccesses an array element based on a user controlled offset. 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. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mqh2-9wrp-vx84 - https://github.com/tensorflow/tensorflow/commit/8ba6fa29cd8bf9cef9b718dc31c78c73081f5b31
CVE ID: CVE-2021-29559 State: PUBLISHED Published: 2021-05-14T19:17:30 Last Updated: 2024-08-03T22:11:06.049Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-125 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can access data outside of bounds of heap allocated array in `tf.raw_ops.UnicodeEncode`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/472c1f12ad9063405737679d4f6bd43094e1d36d/tensorflow/core/kernels/unicode_ops.cc) assumes that the `input_value`/`input_splits` pair specify a valid sparse tensor. The fix will be included in
de_ops.cc) assumes that the `input_value`/`input_splits` pair specify a valid sparse tensor. 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. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-59q2-x2qc-4c97 - https://github.com/tensorflow/tensorflow/commit/51300ba1cc2f487aefec6e6631fef03b0e08b298
CVE ID: CVE-2021-29560 State: PUBLISHED Published: 2021-05-14T19:17:24 Last Updated: 2024-08-03T22:11:05.665Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-125 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `tf.raw_ops.RaggedTensorToTensor`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/d94227d43aa125ad8b54115c03cece54f6a1977b/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L219-L222) uses the same index to access two arrays in parallel. Since the user controls the shape of the input a
_op.cc#L219-L222) uses the same index to access two arrays in parallel. Since the user controls the shape of the input arguments, an attacker could trigger a heap OOB access when `parent_output_index` is shorter than `row_split`. 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. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8gv3-57p6-g35r - https://github.com/tensorflow/tensorflow/commit/a84358aa12f0b1518e606095ab9cfddbf597c121
CVE ID: CVE-2021-29561 State: PUBLISHED Published: 2021-05-14T19:17:19 Last Updated: 2024-08-03T22:11:06.084Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-617 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from `tf.raw_ops.LoadAndRemapMatrix`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/d94227d43aa125ad8b54115c03cece54f6a1977b/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L219-L222) assumes that the `ckpt_path` is always a valid scalar. However, an
core/kernels/ragged_tensor_to_tensor_op.cc#L219-L222) assumes that the `ckpt_path` is always a valid scalar. However, an attacker can send any other tensor as the first argument of `LoadAndRemapMatrix`. This would cause the rank `CHECK` in `scalar<T>()()` to trigger and terminate the process. 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. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gvm4-h8j3-rjrq - https://github.com/tensorflow/tensorflow/
s://github.com/tensorflow/tensorflow/security/advisories/GHSA-gvm4-h8j3-rjrq - https://github.com/tensorflow/tensorflow/commit/77dd114513d7796e1e2b8aece214a380af26fbf4
CVE ID: CVE-2021-29562 State: PUBLISHED Published: 2021-05-14T19:17:12 Last Updated: 2024-08-03T22:11:06.083Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-617 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from the implementation of `tf.raw_ops.IRFFT`. 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. Additional Analyst Notes: -
sorFlow 2.2.3 and TensorFlow 2.1.4, 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-36vm-xw34-x4pj - https://github.com/tensorflow/tensorflow/commit/1c56f53be0b722ca657cbc7df461ed676c8642a2
CVE ID: CVE-2021-29563 State: PUBLISHED Published: 2021-05-14T19:17:07 Last Updated: 2024-08-03T22:11:06.263Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-617 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from the implementation of `tf.raw_ops.RFFT`. Eigen code operating on an empty matrix can trigger on an assertion and will cause program termination. 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
ded 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. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-ph87-fvjr-v33w - https://github.com/tensorflow/tensorflow/commit/31bd5026304677faa8a0b77602c6154171b9aec1
CVE ID: CVE-2021-29564 State: PUBLISHED Published: 2021-05-14T19:17:01 Last Updated: 2024-08-03T22:11:06.243Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-476 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.EditDistance`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/79865b542f9ffdc9caeb255631f7c56f1d4b6517/tensorflow/core/kernels/edit_distance_op.cc#L103-L159) has incomplete validation of the input parameters. The fix will be included in TensorFlow 2.
t_distance_op.cc#L103-L159) has incomplete validation of the input parameters. 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. Additional Analyst Notes: - CVE Program Container: References: - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-75f6-78jr-4656 - https://github.com/tensorflow/tensorflow/commit/f4c364a5d6880557f6f5b6eb5cee2c407f0186b3
CVE ID: CVE-2021-29565 State: PUBLISHED Published: 2021-05-14T19:16:56 Last Updated: 2024-08-03T22:11:06.248Z Severity: LOW (CVSS 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L) Vendors: tensorflow Products: tensorflow Problem Types: CWE-476 Description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.SparseFillEmptyRows`. This is because of missing validation(https://github.com/tensorflow/tensorflow/blob/fdc82089d206e281c628a93771336bf87863d5e8/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L230-L231) that was covered under a `TODO`. If the `dense_shape` tensor is empty, th