{"id":"CVE-2022-35971","aliases":["BIT-tensorflow-2022-35971","EUVD-2022-6757","GHSA-9fpg-838v-wpv7","PYSEC-2026-3150","PYSEC-2026-3305","PYSEC-2026-977","openSUSE-SU-2024:12355-1"],"status":"published","title":"`CHECK` fail in `FakeQuantWithMinMaxVars` in TensorFlow","description":"TensorFlow is an open source platform for machine learning. If `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.","severity":{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium","assessor":"cna","from":"cve"},"epss":{"day":"2026-11-08","score":0.00462,"percentile":0.40263,"model":"v2026.06.15"},"facts":{"in_kev":false,"known_exploited":false,"public_exploit":false,"fix_available":true},"cwes":["CWE-617"],"published":"2022-09-16T20:50:10Z","modified":"2026-10-28T10:27:03Z","fixes":[{"ecosystem":"PyPI","package":"tensorflow","fixed_in":["2.7.2","2.8.1","2.9.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-cpu","fixed_in":["2.7.2","2.8.1","2.9.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-gpu","fixed_in":["2.9.1","2.7.2","2.8.1"],"sources":["ghsa","osv"]},{"ecosystem":"Bitnami","package":"tensorflow","fixed_in":["2.7.2","2.8.1","2.9.1"],"sources":["osv"]}],"affected":[{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.7.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.9.0"},{"fixed":"2.9.1"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.7.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.9.0"},{"fixed":"2.9.1"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.9.0"},{"fixed":"2.9.1"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.7.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}]},{"source":"osv","ecosystem":"Bitnami","package":"tensorflow","ranges":[{"type":"SEMVER","events":[{"introduced":"2.7.0"},{"fixed":"2.7.2"},{"introduced":"2.8.0"},{"fixed":"2.8.1"},{"introduced":"2.9.0"},{"fixed":"2.9.1"}]}]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.7.2"}]}],"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","2.3.4","2.4.0","2.4.1","2.4.2","2.4.3","2.4.4","2.5.0","2.5.1","2.5.2","2.5.3","2.6.0","2.6.0rc0","2.6.0rc1","2.6.0rc2","2.6.1","2.6.2","2.6.3","2.6.4","2.6.5","2.7.0","2.7.0rc0","2.7.0rc1","2.7.1"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}],"versions":["2.8.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.9.0"},{"fixed":"2.9.1"}]}],"versions":["2.9.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.7.2"}]}],"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","2.3.4","2.4.0","2.4.1","2.4.2","2.4.3","2.4.4","2.5.0","2.5.1","2.5.2","2.5.3","2.6.0","2.6.1","2.6.2","2.6.3","2.6.4","2.6.5","2.7.0","2.7.1"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}],"versions":["2.8.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.9.0"},{"fixed":"2.9.1"}]}],"versions":["2.9.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.9.0"},{"fixed":"2.9.1"}]}],"versions":["2.9.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.7.2"}]}],"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","2.3.4","2.4.0","2.4.1","2.4.2"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Party Advisory","advisory","fix","web"]},{"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9fpg-838v-wpv7","tags":["x_refsource_CONFIRM","x_transferred","Patch","Third Party Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0","tags":["web"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2022-35971","tags":["web","advisory"]},{"url":"https://github.com/advisories/GHSA-9fpg-838v-wpv7","tags":["advisory"]},{"url":"https://github.com/CVEProject/cvelistV5/tree/main/cves/2022/35xxx/CVE-2022-35971.json","tags":["advisory"]},{"url":"https://github.com/tensorflow/tensorflow","tags":["package"]},{"url":"https://pypi.org/project/tensorflow","tags":["package"]},{"url":"https://pypi.org/project/tensorflow-cpu","tags":["package"]},{"url":"https://pypi.org/project/tensorflow-gpu","tags":["package"]},{"url":"","tags":["advisory"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35934","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35935","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35937","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35938","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35939","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35940","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35941","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35952","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35959","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35960","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35963","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35964","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35965","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35966","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35967","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35968","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35969","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35970","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35971","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35972","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35973","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35974","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35979","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35981","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35982","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35983","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35984","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35985","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35986","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35987","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35988","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35989","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35990","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35991","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35992","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35993","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35994","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35995","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35996","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35997","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35998","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35999","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36000","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36001","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36002","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36003","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36004","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36005","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36011","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36012","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36013","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36014","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36015","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36016","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36017","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36018","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36019","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36026","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36027","tags":["web"]}],"sources":{"cve":[{"id":"CVE-2022-35971","title":"`CHECK` fail in `FakeQuantWithMinMaxVars` in TensorFlow","description":"TensorFlow is an open source platform for machine learning. If `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.","status":"published","published":"2022-09-16T20:50:10Z","modified":"2025-04-23T17:02:54.713Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium","assessor":"cna"}],"cwes":["CWE-617"],"updated_at":"2026-11-02T14:34:39.935681Z"}],"euvd":[{"id":"EUVD-2022-6757","description":"TensorFlow is an open source platform for machine learning. If `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.","status":"published","published":"2022-09-16T20:50:10Z","modified":"2025-04-23T17:02:54Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"updated_at":"2026-11-02T20:52:11.440801Z"}],"ghsa":[{"id":"GHSA-9fpg-838v-wpv7","title":" TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVars`","description":"### Impact\nIf `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack.\n```python\nimport tensorflow as tf\n\nnum_bits = 8\nnarrow_range = False\ninputs = tf.constant(0, shape=[2,3], dtype=tf.float32)\nmin = tf.constant(0, shape=[2,3], dtype=tf.float32)\nmax = tf.constant(0, shape=[2,3], dtype=tf.float32)\ntf.raw_ops.FakeQuantWithMinMaxVars(inputs=inputs, min=min, max=max, num_bits=num_bits, narrow_range=narrow_range)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [785d67a78a1d533759fcd2f5e8d6ef778de849e0](https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0).\n\nThe fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.\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:\n - Neophytos Christou, Secure Systems Labs, Brown University.\n - 刘力源, Information System \u0026 Security and Countermeasures Experiments Center, Beijing Institute of Technology\n","status":"published","published":"2022-09-16T22:20:09Z","modified":"2023-01-28T05:02:54Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"cwes":["CWE-617"],"updated_at":"2026-11-02T14:36:23.433782Z"}],"nvd":[{"id":"CVE-2022-35971","description":"TensorFlow is an open source platform for machine learning. If `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.","status":"published","published":"2022-09-16T21:15:09.36Z","modified":"2026-06-17T04:52:37.653Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium","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-617"],"updated_at":"2026-11-02T14:07:28.118799Z"}],"osv":[{"id":"CVE-2022-35971","title":"`CHECK` fail in `FakeQuantWithMinMaxVars` in TensorFlow","description":"TensorFlow is an open source platform for machine learning. If `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.","status":"published","published":"2022-09-16T20:50:10Z","modified":"2026-10-28T10:27:03.157183632Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"cwes":["CWE-617"],"updated_at":"2026-11-02T15:44:26.195407Z"},{"id":"GHSA-9fpg-838v-wpv7","title":" TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVars`","description":"### Impact\nIf `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack.\n```python\nimport tensorflow as tf\n\nnum_bits = 8\nnarrow_range = False\ninputs = tf.constant(0, shape=[2,3], dtype=tf.float32)\nmin = tf.constant(0, shape=[2,3], dtype=tf.float32)\nmax = tf.constant(0, shape=[2,3], dtype=tf.float32)\ntf.raw_ops.FakeQuantWithMinMaxVars(inputs=inputs, min=min, max=max, num_bits=num_bits, narrow_range=narrow_range)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [785d67a78a1d533759fcd2f5e8d6ef778de849e0](https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0).\n\nThe fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.\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:\n - Neophytos Christou, Secure Systems Labs, Brown University.\n - 刘力源, Information System \u0026 Security and Countermeasures Experiments Center, Beijing Institute of Technology\n","status":"published","published":"2022-09-16T22:20:09Z","modified":"2026-07-13T16:43:40.8973785Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"cwes":["CWE-617"],"updated_at":"2026-11-02T15:46:43.524801Z"},{"id":"PYSEC-2026-3150","title":" TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVars`","description":"### Impact\nIf `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack.\n```python\nimport tensorflow as tf\n\nnum_bits = 8\nnarrow_range = False\ninputs = tf.constant(0, shape=[2,3], dtype=tf.float32)\nmin = tf.constant(0, shape=[2,3], dtype=tf.float32)\nmax = tf.constant(0, shape=[2,3], dtype=tf.float32)\ntf.raw_ops.FakeQuantWithMinMaxVars(inputs=inputs, min=min, max=max, num_bits=num_bits, narrow_range=narrow_range)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [785d67a78a1d533759fcd2f5e8d6ef778de849e0](https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0).\n\nThe fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.\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:\n - Neophytos Christou, Secure Systems Labs, Brown University.\n - 刘力源, Information System \u0026 Security and Countermeasures Experiments Center, Beijing Institute of Technology\n","status":"published","published":"2026-07-13T14:19:48.554174Z","modified":"2026-07-13T16:43:40.8973785Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"updated_at":"2026-11-02T15:52:56.429374Z"},{"id":"PYSEC-2026-3305","title":" TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVars`","description":"### Impact\nIf `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack.\n```python\nimport tensorflow as tf\n\nnum_bits = 8\nnarrow_range = False\ninputs = tf.constant(0, shape=[2,3], dtype=tf.float32)\nmin = tf.constant(0, shape=[2,3], dtype=tf.float32)\nmax = tf.constant(0, shape=[2,3], dtype=tf.float32)\ntf.raw_ops.FakeQuantWithMinMaxVars(inputs=inputs, min=min, max=max, num_bits=num_bits, narrow_range=narrow_range)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [785d67a78a1d533759fcd2f5e8d6ef778de849e0](https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0).\n\nThe fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.\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:\n - Neophytos Christou, Secure Systems Labs, Brown University.\n - 刘力源, Information System \u0026 Security and Countermeasures Experiments Center, Beijing Institute of Technology\n","status":"published","published":"2026-07-13T14:19:48.681636Z","modified":"2026-07-13T16:43:40.8973785Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"updated_at":"2026-11-02T15:52:56.847083Z"},{"id":"PYSEC-2026-977","title":" TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVars`","description":"### Impact\nIf `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack.\n```python\nimport tensorflow as tf\n\nnum_bits = 8\nnarrow_range = False\ninputs = tf.constant(0, shape=[2,3], dtype=tf.float32)\nmin = tf.constant(0, shape=[2,3], dtype=tf.float32)\nmax = tf.constant(0, shape=[2,3], dtype=tf.float32)\ntf.raw_ops.FakeQuantWithMinMaxVars(inputs=inputs, min=min, max=max, num_bits=num_bits, narrow_range=narrow_range)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [785d67a78a1d533759fcd2f5e8d6ef778de849e0](https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0).\n\nThe fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.\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:\n - Neophytos Christou, Secure Systems Labs, Brown University.\n - 刘力源, Information System \u0026 Security and Countermeasures Experiments Center, Beijing Institute of Technology\n","status":"published","published":"2026-07-07T10:17:21.301041Z","modified":"2026-07-13T16:43:40.8973785Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"updated_at":"2026-11-02T15:52:58.117212Z"},{"id":"BIT-tensorflow-2022-35971","title":"`CHECK` fail in `FakeQuantWithMinMaxVars` in TensorFlow","description":"TensorFlow is an open source platform for machine learning. If `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.","status":"published","published":"2024-03-06T11:13:42.877Z","modified":"2026-09-08T08:48:20.350778809Z","updated_at":"2026-11-02T15:28:35.51001Z"},{"id":"openSUSE-SU-2024:12355-1","title":"tensorflow-lite-2.10.0-1.1 on GA media","description":"These are all security issues fixed in the tensorflow-lite-2.10.0-1.1 package on the GA media of openSUSE Tumbleweed.","status":"published","published":"2024-06-15T00:00:00Z","modified":"2026-02-04T02:37:03.870689Z","updated_at":"2026-11-02T16:58:35.751245Z"}]}}