CVSS: 5.5EPSS: 0%CPEs: 4EXPL: 1CVE-2021-29548 – Division by 0 in `QuantizedBatchNormWithGlobalNormalization`
https://notcve.org/view.php?id=CVE-2021-29548
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 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. • https://github.com/tensorflow/tensorflow/commit/d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p45v-v4pw-77jr • CWE-369: Divide By Zero •
CVSS: 5.5EPSS: 0%CPEs: 4EXPL: 1CVE-2021-29549 – Division by 0 in `QuantizedAdd`
https://notcve.org/view.php?id=CVE-2021-29549
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 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. • https://github.com/tensorflow/tensorflow/commit/744009c9e5cc5d0447f0dc39d055f917e1fd9e16 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x83m-p7pv-ch8v • CWE-369: Divide By Zero •
CVSS: 5.5EPSS: 0%CPEs: 4EXPL: 1CVE-2021-29550 – Division by 0 in `FractionalAvgPool`
https://notcve.org/view.php?id=CVE-2021-29550
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 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. • https://github.com/tensorflow/tensorflow/commit/548b5eaf23685d86f722233d8fbc21d0a4aecb96 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f78g-q7r4-9wcv • CWE-369: Divide By Zero •
CVSS: 5.5EPSS: 0%CPEs: 4EXPL: 1CVE-2021-29551 – OOB read in `MatrixTriangularSolve`
https://notcve.org/view.php?id=CVE-2021-29551
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 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. TensorFlow es una plataforma de código abierto de extremo a extremo para el aprendizaje automático. • https://github.com/tensorflow/tensorflow/commit/480641e3599775a8895254ffbc0fc45621334f68 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vqw6-72r7-fgw7 • CWE-125: Out-of-bounds Read •
CVSS: 5.5EPSS: 0%CPEs: 4EXPL: 1CVE-2021-29552 – CHECK-failure in `UnsortedSegmentJoin`
https://notcve.org/view.php?id=CVE-2021-29552
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. 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. • https://github.com/tensorflow/tensorflow/commit/704866eabe03a9aeda044ec91a8d0c83fc1ebdbe https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jhq9-wm9m-cf89 • CWE-617: Reachable Assertion •