{"id":"CVE-2023-25669","aliases":["AZL-31207","AZL-35314","BIT-tensorflow-2023-25669","EUVD-2023-1095","GHSA-rcf8-g8jv-vg6p","PYSEC-2026-1964","PYSEC-2026-3236","PYSEC-2026-3366"],"status":"published","title":"TensorFlow has Floating Point Exception in AvgPoolGrad with XLA","description":"TensorFlow is an open source platform for machine learning. Prior to versions 2.12.0 and 2.11.1, if the stride and window size are not positive for `tf.raw_ops.AvgPoolGrad`, it can give a floating point exception. A fix is included in TensorFlow version 2.12.0 and version 2.11.1.","severity":{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high","assessor":"cna","from":"cve"},"epss":{"day":"2026-11-10","score":0.00394,"percentile":0.33922,"model":"v2026.06.15"},"facts":{"in_kev":false,"known_exploited":false,"public_exploit":false,"fix_available":true},"cwes":["CWE-697"],"published":"2023-03-24T21:56:53Z","modified":"2026-10-28T10:31:53Z","fixes":[{"ecosystem":"PyPI","package":"tensorflow","fixed_in":["2.11.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-cpu","fixed_in":["2.11.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-gpu","fixed_in":["2.11.1"],"sources":["ghsa","osv"]},{"ecosystem":"Azure Linux:2","package":"tensorflow","fixed_in":["2.11.1-1"],"sources":["osv"]},{"ecosystem":"Azure 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Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/1295ae4dbb52fe06b19733b0257e2340d7b63b8d","tags":["x_refsource_MISC","x_transferred","Patch","fix","web"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2023-25669","tags":["web","advisory"]},{"url":"https://github.com/advisories/GHSA-rcf8-g8jv-vg6p","tags":["advisory"]},{"url":"https://github.com/CVEProject/cvelistV5/tree/main/cves/2023/25xxx/CVE-2023-25669.json","tags":["advisory"]},{"url":"https://github.com/tensorflow/tensorflow","tags":["package"]},{"url":"https://pypi.org/project/tensorflow-gpu","tags":["package"]},{"url":"https://pypi.org/project/tensorflow","tags":["package"]},{"url":"https://pypi.org/project/tensorflow-cpu","tags":["package"]}],"sources":{"cve":[{"id":"CVE-2023-25669","title":"TensorFlow has Floating Point Exception in AvgPoolGrad with XLA","description":"TensorFlow is an open source platform for machine learning. Prior to versions 2.12.0 and 2.11.1, if the stride and window size are not positive for `tf.raw_ops.AvgPoolGrad`, it can give a floating point exception. A fix is included in TensorFlow version 2.12.0 and version 2.11.1.\n","status":"published","published":"2023-03-24T23:32:57.394Z","modified":"2025-02-19T20:33:36.588Z","cvss":[{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high","assessor":"cna"}],"cwes":["CWE-697"],"updated_at":"2026-11-02T14:35:19.559321Z"}],"euvd":[{"id":"EUVD-2023-1095","description":"TensorFlow is an open source platform for machine learning. Prior to versions 2.12.0 and 2.11.1, if the stride and window size are not positive for `tf.raw_ops.AvgPoolGrad`, it can give a floating point exception. A fix is included in TensorFlow version 2.12.0 and version 2.11.1.\n","status":"published","published":"2023-03-24T23:32:57Z","modified":"2025-02-19T20:33:36Z","cvss":[{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high"}],"updated_at":"2026-11-02T20:53:26.792701Z"}],"ghsa":[{"id":"GHSA-rcf8-g8jv-vg6p","title":"TensorFlow has Floating Point Exception in AvgPoolGrad with XLA","description":"### Impact\nIf the stride and window size are not positive for `tf.raw_ops.AvgPoolGrad`, it can give an FPE.\n\n```python\nimport tensorflow as tf\nimport numpy as np\n\n@tf.function(jit_compile=True)\ndef test():\n   y = tf.raw_ops.AvgPoolGrad(orig_input_shape=[1,0,0,0], grad=[[[[0.39117979]]]], ksize=[1,0,0,0], strides=[1,0,0,0], padding=\"SAME\", data_format=\"NCHW\")\n   return y\n\nprint(test())\n```\n\n### Patches\nWe have patched the issue in GitHub commit [1295ae4dbb52fe06b19733b0257e2340d7b63b8d](https://github.com/tensorflow/tensorflow/commit/1295ae4dbb52fe06b19733b0257e2340d7b63b8d).\n\nThe fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.\n\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\n### Attribution\nThis vulnerability has been reported by r3pwnx of 360 AIVul Team\n","status":"published","published":"2023-03-24T21:56:53Z","modified":"2023-03-30T22:16:24Z","cvss":[{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high"}],"cwes":["CWE-697"],"updated_at":"2026-11-02T14:36:48.905887Z"}],"nvd":[{"id":"CVE-2023-25669","description":"TensorFlow is an open source platform for machine learning. Prior to versions 2.12.0 and 2.11.1, if the stride and window size are not positive for `tf.raw_ops.AvgPoolGrad`, it can give a floating point exception. A fix is included in TensorFlow version 2.12.0 and version 2.11.1.\n","status":"published","published":"2023-03-25T00:15:07.653Z","modified":"2026-06-17T05:41:42.197Z","cvss":[{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high","assessor":"secondary"},{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high","assessor":"primary"}],"cwes":["CWE-697"],"updated_at":"2026-11-02T14:07:50.908252Z"}],"osv":[{"id":"AZL-31207","title":"CVE-2023-25669 affecting package tensorflow for versions less than 2.11.1-1","description":"TensorFlow is an open source platform for machine learning. Prior to versions 2.12.0 and 2.11.1, if the stride and window size are not positive for `tf.raw_ops.AvgPoolGrad`, it can give a floating point exception. A fix is included in TensorFlow version 2.12.0 and version 2.11.1.\n","status":"published","published":"2023-03-25T00:15:07Z","modified":"2026-04-21T04:26:09.352954Z","cvss":[{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high"}],"updated_at":"2026-11-02T15:28:03.46006Z"},{"id":"AZL-35314","title":"CVE-2023-25669 affecting package tensorflow for versions less than 2.11.1-1","description":"TensorFlow is an open source platform for machine learning. Prior to versions 2.12.0 and 2.11.1, if the stride and window size are not positive for `tf.raw_ops.AvgPoolGrad`, it can give a floating point exception. A fix is included in TensorFlow version 2.12.0 and version 2.11.1.\n","status":"published","published":"2023-03-25T00:15:07Z","modified":"2026-04-21T04:33:42.24058Z","cvss":[{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high"}],"updated_at":"2026-11-02T15:28:04.173658Z"},{"id":"CVE-2023-25669","title":"TensorFlow has Floating Point Exception in AvgPoolGrad with XLA","description":"TensorFlow is an open source platform for machine learning. Prior to versions 2.12.0 and 2.11.1, if the stride and window size are not positive for `tf.raw_ops.AvgPoolGrad`, it can give a floating point exception. A fix is included in TensorFlow version 2.12.0 and version 2.11.1.\n","status":"published","published":"2023-03-24T23:32:57.394Z","modified":"2026-10-28T10:31:53.078051191Z","cvss":[{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high"}],"cwes":["CWE-697"],"updated_at":"2026-11-02T15:44:31.135751Z"},{"id":"GHSA-rcf8-g8jv-vg6p","title":"TensorFlow has Floating Point Exception in AvgPoolGrad with XLA","description":"### Impact\nIf the stride and window size are not positive for `tf.raw_ops.AvgPoolGrad`, it can give an FPE.\n\n```python\nimport tensorflow as tf\nimport numpy as np\n\n@tf.function(jit_compile=True)\ndef test():\n   y = tf.raw_ops.AvgPoolGrad(orig_input_shape=[1,0,0,0], grad=[[[[0.39117979]]]], ksize=[1,0,0,0], strides=[1,0,0,0], padding=\"SAME\", data_format=\"NCHW\")\n   return y\n\nprint(test())\n```\n\n### Patches\nWe have patched the issue in GitHub commit [1295ae4dbb52fe06b19733b0257e2340d7b63b8d](https://github.com/tensorflow/tensorflow/commit/1295ae4dbb52fe06b19733b0257e2340d7b63b8d).\n\nThe fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.\n\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\n### Attribution\nThis vulnerability has been reported by r3pwnx of 360 AIVul Team\n","status":"published","published":"2023-03-24T21:56:53Z","modified":"2026-09-10T03:49:56.991538651Z","cvss":[{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high"}],"cwes":["CWE-697"],"updated_at":"2026-11-02T15:46:55.877614Z"},{"id":"PYSEC-2026-1964","title":"TensorFlow has Floating Point Exception in AvgPoolGrad with XLA","description":"### Impact\nIf the stride and window size are not positive for `tf.raw_ops.AvgPoolGrad`, it can give an FPE.\n\n```python\nimport tensorflow as tf\nimport numpy as np\n\n@tf.function(jit_compile=True)\ndef test():\n   y = tf.raw_ops.AvgPoolGrad(orig_input_shape=[1,0,0,0], grad=[[[[0.39117979]]]], ksize=[1,0,0,0], strides=[1,0,0,0], padding=\"SAME\", data_format=\"NCHW\")\n   return y\n\nprint(test())\n```\n\n### Patches\nWe have patched the issue in GitHub commit [1295ae4dbb52fe06b19733b0257e2340d7b63b8d](https://github.com/tensorflow/tensorflow/commit/1295ae4dbb52fe06b19733b0257e2340d7b63b8d).\n\nThe fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.\n\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\n### Attribution\nThis vulnerability has been reported by r3pwnx of 360 AIVul Team\n","status":"published","published":"2026-07-07T11:45:16.737184Z","modified":"2026-07-13T16:42:34.087776502Z","cvss":[{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high"}],"updated_at":"2026-11-02T15:52:55.537808Z"},{"id":"PYSEC-2026-3236","title":"TensorFlow has Floating Point Exception in AvgPoolGrad with XLA","description":"### Impact\nIf the stride and window size are not positive for `tf.raw_ops.AvgPoolGrad`, it can give an FPE.\n\n```python\nimport tensorflow as tf\nimport numpy as np\n\n@tf.function(jit_compile=True)\ndef test():\n   y = tf.raw_ops.AvgPoolGrad(orig_input_shape=[1,0,0,0], grad=[[[[0.39117979]]]], ksize=[1,0,0,0], strides=[1,0,0,0], padding=\"SAME\", data_format=\"NCHW\")\n   return y\n\nprint(test())\n```\n\n### Patches\nWe have patched the issue in GitHub commit [1295ae4dbb52fe06b19733b0257e2340d7b63b8d](https://github.com/tensorflow/tensorflow/commit/1295ae4dbb52fe06b19733b0257e2340d7b63b8d).\n\nThe fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.\n\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\n### Attribution\nThis vulnerability has been reported by r3pwnx of 360 AIVul Team\n","status":"published","published":"2026-07-13T14:19:59.194088Z","modified":"2026-07-13T16:42:34.087776502Z","cvss":[{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high"}],"updated_at":"2026-11-02T15:52:56.429374Z"},{"id":"PYSEC-2026-3366","title":"TensorFlow has Floating Point Exception in AvgPoolGrad with XLA","description":"### Impact\nIf the stride and window size are not positive for `tf.raw_ops.AvgPoolGrad`, it can give an FPE.\n\n```python\nimport tensorflow as tf\nimport numpy as np\n\n@tf.function(jit_compile=True)\ndef test():\n   y = tf.raw_ops.AvgPoolGrad(orig_input_shape=[1,0,0,0], grad=[[[[0.39117979]]]], ksize=[1,0,0,0], strides=[1,0,0,0], padding=\"SAME\", data_format=\"NCHW\")\n   return y\n\nprint(test())\n```\n\n### Patches\nWe have patched the issue in GitHub commit [1295ae4dbb52fe06b19733b0257e2340d7b63b8d](https://github.com/tensorflow/tensorflow/commit/1295ae4dbb52fe06b19733b0257e2340d7b63b8d).\n\nThe fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.\n\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\n### Attribution\nThis vulnerability has been reported by r3pwnx of 360 AIVul Team\n","status":"published","published":"2026-07-13T14:19:59.302904Z","modified":"2026-07-13T16:42:34.087776502Z","cvss":[{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high"}],"updated_at":"2026-11-02T15:52:56.847083Z"},{"id":"BIT-tensorflow-2023-25669","title":"TensorFlow has Floating Point Exception in AvgPoolGrad with XLA","description":"TensorFlow is an open source platform for machine learning. Prior to versions 2.12.0 and 2.11.1, if the stride and window size are not positive for `tf.raw_ops.AvgPoolGrad`, it can give a floating point exception. A fix is included in TensorFlow version 2.12.0 and version 2.11.1.","status":"published","published":"2024-03-06T11:08:20.897Z","modified":"2026-09-08T08:48:20.554458357Z","updated_at":"2026-11-02T15:28:36.104787Z"}]}}