{"id":"CVE-2021-29512","aliases":["BIT-tensorflow-2021-29512","GHSA-4278-2v5v-65r4","PYSEC-2021-149","PYSEC-2021-440","PYSEC-2021-638"],"url":"https://o3.security/vulnerability/CVE-2021-29512","summary":"Heap buffer overflow in `RaggedBinCount`","details":"### Impact\nIf the `splits` argument of `RaggedBincount` does not specify a valid [`SparseTensor`](https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor), then an attacker can trigger a heap buffer overflow:\n\n```python\nimport tensorflow as tf\ntf.raw_ops.RaggedBincount(splits=[0], values=[1,1,1,1,1], size=5, weights=[1,2,3,4], binary_output=False)\n```\n\nThis will cause a read from outside the bounds of the `splits` tensor buffer in the [implementation of the `RaggedBincount` op](https://github.com/tensorflow/tensorflow/blob/8b677d79167799f71c42fd3fa074476e0295413a/tensorflow/core/kernels/bincount_op.cc#L430-L433):\n\n```cc\n    for (int idx = 0; idx < num_values; ++idx) {\n      while (idx >= splits(batch_idx)) {\n        batch_idx++;\n      }\n      ...\n    }\n```\n\nBefore the `for` loop, `batch_idx` is set to 0. The user controls the `splits` array, making it contain only one element, 0. Thus, the code in the `while` loop would increment `batch_idx` and then try to read `splits(1)`, which is outside of bounds.\n\n### Patches\nWe have patched the issue in GitHub commit [eebb96c2830d48597d055d247c0e9aebaea94cd5](https://github.com/tensorflow/tensorflow/commit/eebb96c2830d48597d055d247c0e9aebaea94cd5).\n\nThe fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3, as these are 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.","published":"2021-05-14T19:15:07.753Z","modified":"2026-08-07T17:31:53.300235Z","cvss":{"score":7.8,"severity":"HIGH","vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H"},"epss":null,"cisaKev":null,"exploitsKnown":null,"affectedPackages":[{"ecosystem":"PyPI","name":"tensorflow","fixedVersion":"2.3.3"},{"ecosystem":"PyPI","name":"tensorflow","fixedVersion":"2.4.2"},{"ecosystem":"PyPI","name":"tensorflow-cpu","fixedVersion":"2.3.3"},{"ecosystem":"PyPI","name":"tensorflow-cpu","fixedVersion":"2.4.2"},{"ecosystem":"PyPI","name":"tensorflow-gpu","fixedVersion":"2.3.3"},{"ecosystem":"PyPI","name":"tensorflow-gpu","fixedVersion":"2.4.2"}],"fix":{"url":"https://github.com/tensorflow/tensorflow/commit/eebb96c2830d48597d055d247c0e9aebaea94cd5","label":"tensorflow/tensorflow@eebb96c"},"references":[{"type":"FIX","url":"https://github.com/tensorflow/tensorflow/commit/eebb96c2830d48597d055d247c0e9aebaea94cd5"},{"type":"FIX","url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4278-2v5v-65r4"},{"type":"ADVISORY","url":"https://nvd.nist.gov/vuln/detail/CVE-2021-29512"},{"type":"WEB","url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-440.yaml"},{"type":"WEB","url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-638.yaml"},{"type":"WEB","url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-149.yaml"}],"provenance":{"sources":["OSV.dev","FIRST.org (EPSS)"],"lastVerified":"2026-08-07T17:31:53.300235Z"}}