{"id":"CVE-2021-41211","aliases":["GHSA-cvgx-3v3q-m36c","BIT-tensorflow-2021-41211","PYSEC-2021-403","PYSEC-2021-620","PYSEC-2021-818"],"title":"Heap OOB in shape inference for `QuantizeV2`","summary":"Heap OOB in shape inference for `QuantizeV2`","severity":"high","cvss":7.1,"cvssVector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H","vendor":"tensorflow","product":"tensorflow","ecosystem":"pip","affected":["tensorflow >= 2.6.0, < 2.6.1","tensorflow-cpu >= 2.6.0, < 2.6.1","tensorflow-gpu >= 2.6.0, < 2.6.1"],"patched":["tensorflow 2.6.1","tensorflow-cpu 2.6.1","tensorflow-gpu 2.6.1"],"published":"2021-11-10","updated":"2026-07-08","source":"OSV","sourceUrl":"https://osv.dev/vulnerability/GHSA-cvgx-3v3q-m36c","references":[{"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cvgx-3v3q-m36c"},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2021-41211"},{"url":"https://github.com/tensorflow/tensorflow/commit/a0d64445116c43cf46a5666bd4eee28e7a82f244"},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-620.yaml"},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-818.yaml"},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-403.yaml"},{"url":"https://github.com/tensorflow/tensorflow"}],"tags":["osv","pip"],"epss":0.00208,"epssPercentile":0.11234,"ingestedAt":"2026-07-08T18:25:48.579Z","slug":"CVE-2021-41211","body":"## Overview\n\n### Impact\nThe [shape inference code for `QuantizeV2`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/framework/common_shape_fns.cc#L2509-L2530) can trigger a read outside of bounds of heap allocated array:\n\n```python\nimport tensorflow as tf\n\n@tf.function\ndef test():\n  data=tf.raw_ops.QuantizeV2(\n    input=[1.0,1.0],\n    min_range=[1.0,10.0],\n    max_range=[1.0,10.0],\n    T=tf.qint32,\n    mode='MIN_COMBINED',\n    round_mode='HALF_TO_EVEN',\n    narrow_range=False,\n    axis=-100,\n    ensure_minimum_range=10)\n  return data\n\ntest()\n```\n\nThis occurs whenever `axis` is a negative value less than `-1`. In this case, we are accessing data before the start of a heap buffer:\n    \n```cc\nint axis = -1;\nStatus s = c->GetAttr(\"axis\", &axis);\nif (!s.ok() && s.code() != error::NOT_FOUND) {\n  return s;\n}   \n... \nif (axis != -1) {\n  ...\n  TF_RETURN_IF_ERROR(\n      c->Merge(c->Dim(minmax, 0), c->Dim(input, axis), &depth));\n}\n```\n\nThe code allows `axis` to be an optional argument (`s` would contain an `error::NOT_FOUND` error code). Otherwise, it assumes that `axis` is a valid index into the dimensions of the `input` tensor. If `axis` is less than `-1` then this results in a heap OOB read.\n    \n### Patches\nWe have patched the issue in GitHub commit [a0d64445116c43cf46a5666bd4eee28e7a82f244](https://github.com/tensorflow/tensorflow/commit/a0d64445116c43cf46a5666bd4eee28e7a82f244).\n    \nThe fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.\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.\n\n## Affected packages\n\n- `tensorflow >= 2.6.0, < 2.6.1`\n- `tensorflow-cpu >= 2.6.0, < 2.6.1`\n- `tensorflow-gpu >= 2.6.0, < 2.6.1`\n\n## Remediation\n\nUpgrade to a patched release:\n\n- `tensorflow 2.6.1`\n- `tensorflow-cpu 2.6.1`\n- `tensorflow-gpu 2.6.1`","depth":"twilight","depthScore":39,"depthScoreParts":{"impact":39.1,"likelihood":0,"exploitation":0,"ransomware":0},"changes":[]}