{"id":"GHSA-rf3h-xgv5-2q39","summary":"Division by zero in TFLite's implementation of `DepthwiseConv`","details":"### Impact\nThe implementation of the `DepthwiseConv` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/1a8e885b864c818198a5b2c0cbbeca5a1e833bc8/tensorflow/lite/kernels/depthwise_conv.cc#L287-L288):\n\n```cc\nint num_input_channels = SizeOfDimension(input, 3);\nTF_LITE_ENSURE_EQ(context, num_filter_channels % num_input_channels, 0);\n```\n\nAn attacker can craft a model such that `input`'s fourth dimension would be 0.\n\n### Patches\nWe have patched the issue in GitHub commit [cbda3c6b2dbbd3fbdc482ff8c0170a78ec2e97d0](https://github.com/tensorflow/tensorflow/commit/cbda3c6b2dbbd3fbdc482ff8c0170a78ec2e97d0).\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 members of the Aivul Team from Qihoo 360.","aliases":["BIT-tensorflow-2021-29602","CVE-2021-29602","PYSEC-2021-239","PYSEC-2021-530","PYSEC-2021-728"],"modified":"2026-07-08T06:29:10.556782395Z","published":"2021-05-21T14:28:12Z","database_specific":{"cwe_ids":["CWE-369"],"severity":"LOW","github_reviewed":true,"github_reviewed_at":"2021-05-17T22:29:55Z","nvd_published_at":"2021-05-14T20:15:00Z"},"references":[{"type":"WEB","url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rf3h-xgv5-2q39"},{"type":"ADVISORY","url":"https://nvd.nist.gov/vuln/detail/CVE-2021-29602"},{"type":"WEB","url":"https://github.com/tensorflow/tensorflow/commit/cbda3c6b2dbbd3fbdc482ff8c0170a78ec2e97d0"},{"type":"WEB","url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-530.yaml"},{"type":"WEB","url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-728.yaml"},{"type":"WEB","url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-239.yaml"},{"type":"PACKAGE","url":"https://github.com/tensorflow/tensorflow"},{"type":"WEB","url":"https://github.com/tensorflow/tensorflow/blob/1a8e885b864c818198a5b2c0cbbeca5a1e833bc8/tensorflow/lite/kernels/depthwise_conv.cc#L287-L288"}],"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-rf3h-xgv5-2q39/GHSA-rf3h-xgv5-2q39.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-rf3h-xgv5-2q39/GHSA-rf3h-xgv5-2q39.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-rf3h-xgv5-2q39/GHSA-rf3h-xgv5-2q39.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-rf3h-xgv5-2q39/GHSA-rf3h-xgv5-2q39.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-rf3h-xgv5-2q39/GHSA-rf3h-xgv5-2q39.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-rf3h-xgv5-2q39/GHSA-rf3h-xgv5-2q39.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-rf3h-xgv5-2q39/GHSA-rf3h-xgv5-2q39.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-rf3h-xgv5-2q39/GHSA-rf3h-xgv5-2q39.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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