{"id":"CVE-2021-29544","aliases":["BIT-tensorflow-2021-29544","EUVD-2021-0285","GHSA-6g85-3hm8-83f9","PYSEC-2021-181","PYSEC-2021-472","PYSEC-2021-670"],"status":"published","title":"CHECK-fail in `QuantizeAndDequantizeV4Grad`","description":"TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.QuantizeAndDequantizeV4Grad`. This is because the implementation does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to `QuantizeAndDequantizePerChannelGradientImpl`. However, the `vec\u003cT\u003e` method, requires the rank to 1 and triggers a `CHECK` failure otherwise. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version.","severity":{"version":"3.1","score":2.5,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L","level":"low","assessor":"cna","from":"cve"},"epss":{"day":"2026-11-10","score":0.0031,"percentile":0.24051,"model":"v2026.06.15"},"facts":{"in_kev":false,"known_exploited":false,"public_exploit":false,"fix_available":true},"cwes":["CWE-754"],"published":"2021-05-14T19:11:06Z","modified":"2026-10-20T14:24:27Z","fixes":[{"ecosystem":"PyPI","package":"tensorflow","fixed_in":["2.4.2","2.2.0rc0","2.3.0rc0","2.3.4","2.4.3"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-cpu","fixed_in":["2.4.2","2.2.0rc0","2.3.0rc0","2.3.4","2.4.3"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-gpu","fixed_in":["2.4.2","2.2.0rc0","2.3.0rc0","2.3.4","2.4.3"],"sources":["ghsa","osv"]},{"ecosystem":"Bitnami","package":"tensorflow","fixed_in":["2.4.2"],"sources":["osv"]}],"affected":[{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}]},{"source":"osv","ecosystem":"Bitnami","package":"tensorflow","ranges":[{"type":"SEMVER","events":[{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}],"versions":["2.4.0","2.4.1"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}],"versions":["2.4.0","2.4.1"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}],"versions":["2.4.0","2.4.1"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"GIT","events":[{"introduced":"0"},{"fixed":"20431e9044cf2ad3c0323c34888b192f3289af6b"}]},{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.2.0rc0"},{"introduced":"2.2.0"},{"fixed":"2.3.0rc0"},{"introduced":"2.3.0"},{"fixed":"2.3.4"},{"introduced":"2.4.0"},{"fixed":"2.4.3"}]}],"versions":["0.12.0","0.12.0rc0","0.12.0rc1","0.12.1","1.0.0","1.0.1","1.1.0","1.1.0rc0","1.1.0rc1","1.1.0rc2","1.10.0","1.10.0rc0","1.10.0rc1","1.10.1","1.11.0","1.11.0rc0","1.11.0rc1","1.11.0rc2","1.12.0","1.12.0rc0","1.12.0rc1","1.12.0rc2","1.12.2","1.12.3","1.13.0rc0","1.13.0rc1","1.13.0rc2","1.13.1","1.13.2","1.14.0","1.14.0rc0","1.14.0rc1","1.15.0","1.15.0rc0","1.15.0rc1","1.15.0rc2","1.15.0rc3","1.15.2","1.15.3","1.15.4","1.15.5","1.2.0","1.2.0rc0","1.2.0rc1","1.2.0rc2","1.2.1","1.3.0","1.3.0rc0","1.3.0rc1","1.3.0rc2","1.4.0","1.4.0rc0","1.4.0rc1","1.4.1","1.5.0","1.5.0rc0","1.5.0rc1","1.5.1","1.6.0","1.6.0rc0","1.6.0rc1","1.7.0","1.7.0rc0","1.7.0rc1","1.7.1","1.8.0","1.8.0rc0","1.8.0rc1","1.9.0","1.9.0rc0","1.9.0rc1","1.9.0rc2","2.0.0","2.0.0a0","2.0.0b0","2.0.0b1","2.0.0rc0","2.0.0rc1","2.0.0rc2","2.0.1","2.0.2","2.0.3","2.0.4","2.1.0","2.1.0rc0","2.1.0rc1","2.1.0rc2","2.1.1","2.1.2","2.1.3","2.1.4","2.2.0","2.2.1","2.2.2","2.2.3","2.3.0","2.3.1","2.3.2","2.3.3","2.4.0","2.4.1","2.4.2"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"GIT","events":[{"introduced":"0"},{"fixed":"20431e9044cf2ad3c0323c34888b192f3289af6b"}]},{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.2.0rc0"},{"introduced":"2.2.0"},{"fixed":"2.3.0rc0"},{"introduced":"2.3.0"},{"fixed":"2.3.4"},{"introduced":"2.4.0"},{"fixed":"2.4.3"}]}],"versions":["1.15.0","2.1.0","2.1.1","2.1.2","2.1.3","2.1.4","2.2.0","2.2.1","2.2.2","2.2.3","2.3.0","2.3.1","2.3.2","2.3.3","2.4.0","2.4.1","2.4.2"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"GIT","events":[{"introduced":"0"},{"fixed":"20431e9044cf2ad3c0323c34888b192f3289af6b"}]},{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.2.0rc0"},{"introduced":"2.2.0"},{"fixed":"2.3.0rc0"},{"introduced":"2.3.0"},{"fixed":"2.3.4"},{"introduced":"2.4.0"},{"fixed":"2.4.3"}]}],"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","2.1.4","2.2.0","2.2.1","2.2.2","2.2.3","2.3.0","2.3.1","2.3.2","2.3.3","2.4.0","2.4.1","2.4.2"]}],"products":[{"vendor":"google","product":"tensorflow"},{"vendor":"tensorflow","product":"tensorflow"}],"references":[{"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6g85-3hm8-83f9","tags":["x_refsource_CONFIRM","x_transferred","Exploit","Patch","Third Party Advisory","advisory","fix","web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/20431e9044cf2ad3c0323c34888b192f3289af6b","tags":["x_refsource_MISC","x_transferred","Patch","Third Party Advisory","advisory","fix","web"]},{"url":"https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L162-L163","tags":["x_refsource_MISC","web"]},{"url":"https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.h#L295-L306","tags":["x_refsource_MISC","web"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2021-29544","tags":["web","advisory"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-472.yaml","tags":["web"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-670.yaml","tags":["web"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-181.yaml","tags":["web"]},{"url":"https://github.com/advisories/GHSA-6g85-3hm8-83f9"},{"url":"https://github.com/tensorflow/tensorflow","tags":["package"]}],"sources":{"cve":[{"id":"CVE-2021-29544","title":"CHECK-fail in `QuantizeAndDequantizeV4Grad`","description":"TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.QuantizeAndDequantizeV4Grad`. This is because the implementation does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to `QuantizeAndDequantizePerChannelGradientImpl`. However, the `vec\u003cT\u003e` method, requires the rank to 1 and triggers a `CHECK` failure otherwise. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version.","status":"published","published":"2021-05-14T19:11:06Z","modified":"2024-10-31T20:41:21.258Z","cvss":[{"version":"3.1","score":2.5,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L","level":"low","assessor":"cna"}],"cwes":["CWE-754"],"updated_at":"2026-11-02T14:33:06.658806Z"}],"euvd":[{"id":"EUVD-2021-0285","description":"TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.QuantizeAndDequantizeV4Grad`. This is because the implementation does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to `QuantizeAndDequantizePerChannelGradientImpl`. However, the `vec\u003cT\u003e` method, requires the rank to 1 and triggers a `CHECK` failure otherwise. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version.","status":"published","published":"2021-05-14T19:11:06Z","modified":"2024-10-31T20:41:21Z","cvss":[{"version":"3.1","score":2.5,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L","level":"low"}],"updated_at":"2026-11-03T00:05:13.001555Z"}],"ghsa":[{"id":"GHSA-6g85-3hm8-83f9","title":"CHECK-fail in `QuantizeAndDequantizeV4Grad`","description":"### Impact\nAn attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.QuantizeAndDequantizeV4Grad`:\n\n```python\nimport tensorflow as tf\n\ngradient_tensor = tf.constant([0.0], shape=[1])\ninput_tensor = tf.constant([0.0], shape=[1])\ninput_min = tf.constant([[0.0]], shape=[1, 1])\ninput_max = tf.constant([[0.0]], shape=[1, 1])\n\ntf.raw_ops.QuantizeAndDequantizeV4Grad(\n  gradients=gradient_tensor, input=input_tensor,\n  input_min=input_min, input_max=input_max, axis=0)\n```                     \n                        \nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L162-L163) does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to [`QuantizeAndDequantizePerChannelGradientImpl`](https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.h#L295-L306):\n\n```cc \ntemplate \u003ctypename Device, typename T\u003e\nstruct QuantizeAndDequantizePerChannelGradientImpl {\n  static void Compute(const Device\u0026 d,\n                      typename TTypes\u003cT, 3\u003e::ConstTensor gradient,\n                      typename TTypes\u003cT, 3\u003e::ConstTensor input,\n                      const Tensor* input_min_tensor,\n                      const Tensor* input_max_tensor,\n                      typename TTypes\u003cT, 3\u003e::Tensor input_backprop,\n                      typename TTypes\u003cT\u003e::Flat input_min_backprop,\n                      typename TTypes\u003cT\u003e::Flat input_max_backprop) {\n    ...\n    auto input_min = input_min_tensor-\u003evec\u003cT\u003e();\n    auto input_max = input_max_tensor-\u003evec\u003cT\u003e();\n    ...\n}\n```\n\nHowever, the `vec\u003cT\u003e` method, requires the rank to 1 and triggers a `CHECK` failure otherwise.\n\n### Patches\nWe have patched the issue in GitHub commit [20431e9044cf2ad3c0323c34888b192f3289af6b](https://github.com/tensorflow/tensorflow/commit/20431e9044cf2ad3c0323c34888b192f3289af6b).\n\nThe fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version.\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.","status":"published","published":"2021-05-21T14:23:22Z","modified":"2024-11-19T19:33:16Z","cvss":[{"version":"4.0","score":2,"vector":"CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N","level":"low"},{"version":"3.1","score":2.5,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L","level":"low"}],"cwes":["CWE-754"],"updated_at":"2026-11-02T14:38:21.777721Z"}],"nvd":[{"id":"CVE-2021-29544","description":"TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.QuantizeAndDequantizeV4Grad`. This is because the implementation does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to `QuantizeAndDequantizePerChannelGradientImpl`. However, the `vec\u003cT\u003e` method, requires the rank to 1 and triggers a `CHECK` failure otherwise. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version.","status":"published","published":"2021-05-14T20:15:12.623Z","modified":"2026-06-17T03:47:52.727Z","cvss":[{"version":"3.1","score":2.5,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L","level":"low","assessor":"secondary"},{"version":"3.1","score":5.5,"vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","level":"medium","assessor":"primary"},{"version":"2.0","score":2.1,"vector":"AV:L/AC:L/Au:N/C:N/I:N/A:P","level":"low","assessor":"primary"}],"cwes":["CWE-754"],"updated_at":"2026-11-02T14:06:53.343329Z"}],"osv":[{"id":"CVE-2021-29544","description":"TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.QuantizeAndDequantizeV4Grad`. This is because the implementation does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to `QuantizeAndDequantizePerChannelGradientImpl`. However, the `vec\u003cT\u003e` method, requires the rank to 1 and triggers a `CHECK` failure otherwise. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version.","status":"published","published":"2021-05-14T20:15:12.623Z","modified":"2026-10-20T14:24:27.565416988Z","cvss":[{"version":"3.1","score":5.5,"vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"updated_at":"2026-11-02T15:44:19.129331Z"},{"id":"GHSA-6g85-3hm8-83f9","title":"CHECK-fail in `QuantizeAndDequantizeV4Grad`","description":"### Impact\nAn attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.QuantizeAndDequantizeV4Grad`:\n\n```python\nimport tensorflow as tf\n\ngradient_tensor = tf.constant([0.0], shape=[1])\ninput_tensor = tf.constant([0.0], shape=[1])\ninput_min = tf.constant([[0.0]], shape=[1, 1])\ninput_max = tf.constant([[0.0]], shape=[1, 1])\n\ntf.raw_ops.QuantizeAndDequantizeV4Grad(\n  gradients=gradient_tensor, input=input_tensor,\n  input_min=input_min, input_max=input_max, axis=0)\n```                     \n                        \nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L162-L163) does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to [`QuantizeAndDequantizePerChannelGradientImpl`](https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.h#L295-L306):\n\n```cc \ntemplate \u003ctypename Device, typename T\u003e\nstruct QuantizeAndDequantizePerChannelGradientImpl {\n  static void Compute(const Device\u0026 d,\n                      typename TTypes\u003cT, 3\u003e::ConstTensor gradient,\n                      typename TTypes\u003cT, 3\u003e::ConstTensor input,\n                      const Tensor* input_min_tensor,\n                      const Tensor* input_max_tensor,\n                      typename TTypes\u003cT, 3\u003e::Tensor input_backprop,\n                      typename TTypes\u003cT\u003e::Flat input_min_backprop,\n                      typename TTypes\u003cT\u003e::Flat input_max_backprop) {\n    ...\n    auto input_min = input_min_tensor-\u003evec\u003cT\u003e();\n    auto input_max = input_max_tensor-\u003evec\u003cT\u003e();\n    ...\n}\n```\n\nHowever, the `vec\u003cT\u003e` method, requires the rank to 1 and triggers a `CHECK` failure otherwise.\n\n### Patches\nWe have patched the issue in GitHub commit [20431e9044cf2ad3c0323c34888b192f3289af6b](https://github.com/tensorflow/tensorflow/commit/20431e9044cf2ad3c0323c34888b192f3289af6b).\n\nThe fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version.\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.","status":"published","published":"2021-05-21T14:23:22Z","modified":"2026-07-08T06:28:48.815860815Z","cvss":[{"version":"3.1","score":2.5,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L","level":"low"},{"version":"4.0","score":2,"vector":"CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N","level":"low"}],"cwes":["CWE-754"],"updated_at":"2026-11-02T15:46:39.618611Z"},{"id":"BIT-tensorflow-2021-29544","title":"CHECK-fail in `QuantizeAndDequantizeV4Grad`","description":"TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.QuantizeAndDequantizeV4Grad`. This is because the implementation does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to `QuantizeAndDequantizePerChannelGradientImpl`. However, the `vec\u003cT\u003e` method, requires the rank to 1 and triggers a `CHECK` failure otherwise. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version.","status":"published","published":"2024-03-06T11:19:29.901Z","modified":"2026-09-08T08:48:10.867509092Z","updated_at":"2026-11-02T15:28:35.51001Z"},{"id":"PYSEC-2021-181","description":"TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.QuantizeAndDequantizeV4Grad`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L162-L163) does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to `QuantizeAndDequantizePerChannelGradientImpl`(https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.h#L295-L306). However, the `vec\u003cT\u003e` method, requires the rank to 1 and triggers a `CHECK` failure otherwise. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version.","status":"published","published":"2021-05-14T20:15:00Z","modified":"2023-12-06T01:01:05.139089Z","updated_at":"2026-11-02T15:52:52.682031Z"},{"id":"PYSEC-2021-472","description":"TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.QuantizeAndDequantizeV4Grad`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L162-L163) does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to `QuantizeAndDequantizePerChannelGradientImpl`(https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.h#L295-L306). However, the `vec\u003cT\u003e` method, requires the rank to 1 and triggers a `CHECK` failure otherwise. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version.","status":"published","published":"2021-05-14T20:15:00Z","modified":"2023-12-06T01:01:05.139089Z","updated_at":"2026-11-02T15:52:53.119977Z"},{"id":"PYSEC-2021-670","description":"TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.QuantizeAndDequantizeV4Grad`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L162-L163) does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to `QuantizeAndDequantizePerChannelGradientImpl`(https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.h#L295-L306). However, the `vec\u003cT\u003e` method, requires the rank to 1 and triggers a `CHECK` failure otherwise. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version.","status":"published","published":"2021-05-14T20:15:00Z","modified":"2023-12-06T01:01:05.139089Z","updated_at":"2026-11-02T15:52:53.119977Z"}]}}