CVSS: 5.5EPSS: 0%CPEs: 6EXPL: 0CVE-2021-37646 – Bad alloc in `StringNGrams` caused by integer conversion in TensorFlow
https://notcve.org/view.php?id=CVE-2021-37646
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.StringNGrams` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/string_ngrams_op.cc#L184) calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer. • https://github.com/tensorflow/tensorflow/commit/c283e542a3f422420cfdb332414543b62fc4e4a5 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6jh-7gv5-28vg • CWE-681: Incorrect Conversion between Numeric Types •
CVSS: 5.5EPSS: 0%CPEs: 6EXPL: 0CVE-2021-37661 – Crash caused by integer conversion to unsigned in TensorFlow
https://notcve.org/view.php?id=CVE-2021-37661
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. • https://github.com/tensorflow/tensorflow/commit/8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gf88-j2mg-cc82 • CWE-681: Incorrect Conversion between Numeric Types •
CVSS: 5.5EPSS: 0%CPEs: 6EXPL: 0CVE-2021-37645 – Integer overflow due to conversion to unsigned in TensorFlow
https://notcve.org/view.php?id=CVE-2021-37645
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. • https://github.com/tensorflow/tensorflow/commit/96f364a1ca3009f98980021c4b32be5fdcca33a1 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9w2p-5mgw-p94c • CWE-681: Incorrect Conversion between Numeric Types •
CVSS: 7.8EPSS: 0%CPEs: 6EXPL: 0CVE-2021-37651 – Heap buffer overflow in `FractionalAvgPoolGrad` in TensorFlow
https://notcve.org/view.php?id=CVE-2021-37651
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.FractionalAvgPoolGrad` can be tricked into accessing data outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/fractional_avg_pool_op.cc#L205) does not validate that the input tensor is non-empty. Thus, code constructs an empty `EigenDoubleMatrixMap` and then accesses this buffer with indices that are outside of the empty area. We have patched the issue in GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30. • https://github.com/tensorflow/tensorflow/commit/0f931751fb20f565c4e94aa6df58d54a003cdb30 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hpv4-7p9c-mvfr • CWE-125: Out-of-bounds Read CWE-787: Out-of-bounds Write •
CVSS: 7.8EPSS: 0%CPEs: 6EXPL: 0CVE-2021-37650 – Segfault and heap buffer overflow in `{Experimental,}DatasetToTFRecord` in TensorFlow
https://notcve.org/view.php?id=CVE-2021-37650
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.ExperimentalDatasetToTFRecord` and `tf.raw_ops.DatasetToTFRecord` can trigger heap buffer overflow and segmentation fault. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc#L93-L102) assumes that all records in the dataset are of string type. However, there is no check for that, and the example given above uses numeric types. We have patched the issue in GitHub commit e0b6e58c328059829c3eb968136f17aa72b6c876. • https://github.com/tensorflow/tensorflow/commit/e0b6e58c328059829c3eb968136f17aa72b6c876 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f8h4-7rgh-q2gm • CWE-120: Buffer Copy without Checking Size of Input ('Classic Buffer Overflow') CWE-787: Out-of-bounds Write •