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 •
CVSS: 7.1EPSS: 0%CPEs: 4EXPL: 1CVE-2021-29553 – Heap OOB in `QuantizeAndDequantizeV3`
https://notcve.org/view.php?id=CVE-2021-29553
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 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. • https://github.com/tensorflow/tensorflow/commit/99085e8ff02c3763a0ec2263e44daec416f6a387 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h9px-9vqg-222h • CWE-125: Out-of-bounds Read •
CVSS: 5.5EPSS: 0%CPEs: 4EXPL: 1CVE-2021-29554 – Division by 0 in `DenseCountSparseOutput`
https://notcve.org/view.php?id=CVE-2021-29554
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 division. Since `data` is given by the `values` argument, `num_batch_elements` is 0. The fix will be included in TensorFlow 2.5.0. • https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qg48-85hg-mqc5 • CWE-369: Divide By Zero •