{"id":"CVE-2020-15200","aliases":["GHSA-x7rp-74x2-mjf3","BIT-tensorflow-2020-15200","PYSEC-2020-123","PYSEC-2020-280","PYSEC-2020-315"],"title":"Segfault in Tensorflow","summary":"Segfault in Tensorflow","severity":"medium","cvss":5.9,"cvssVector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","vendor":"tensorflow","product":"tensorflow","ecosystem":"pip","affected":["tensorflow >= 2.3.0, < 2.3.1","tensorflow-cpu >= 2.3.0, < 2.3.1","tensorflow-gpu >= 2.3.0, < 2.3.1"],"patched":["tensorflow 2.3.1","tensorflow-cpu 2.3.1","tensorflow-gpu 2.3.1"],"published":"2020-09-25","updated":"2026-07-08","source":"OSV","sourceUrl":"https://osv.dev/vulnerability/GHSA-x7rp-74x2-mjf3","references":[{"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x7rp-74x2-mjf3"},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2020-15200"},{"url":"https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02"},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-280.yaml"},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-315.yaml"},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-123.yaml"},{"url":"https://github.com/tensorflow/tensorflow"},{"url":"https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"}],"tags":["osv","pip"],"epss":0.00851,"epssPercentile":0.56712,"ingestedAt":"2026-07-08T18:25:54.139Z","slug":"CVE-2020-15200","body":"## Overview\n\n### Impact\nThe `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the [following code](https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L248-L265\n) sets up conditions to cause a heap buffer overflow:\n```cc\n    auto per_batch_counts = BatchedMap<W>(num_batches);\n    int batch_idx = 0;\n    for (int idx = 0; idx < num_values; ++idx) {\n      while (idx >= splits_values(batch_idx)) {\n        batch_idx++;\n      }\n      const auto& value = values_values(idx);\n      if (value >= 0 && (maxlength_ <= 0 || value < maxlength_)) {\n        per_batch_counts[batch_idx - 1][value] = 1;\n      }\n    }\n```\n\nA `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault.\n\n### Patches\nWe have patched the issue in 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and will release a patch release.\n\nWe recommend users to upgrade to TensorFlow 2.3.1.\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 is a variant of [GHSA-p5f8-gfw5-33w4](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4)\n\n## Affected packages\n\n- `tensorflow >= 2.3.0, < 2.3.1`\n- `tensorflow-cpu >= 2.3.0, < 2.3.1`\n- `tensorflow-gpu >= 2.3.0, < 2.3.1`\n\n## Remediation\n\nUpgrade to a patched release:\n\n- `tensorflow 2.3.1`\n- `tensorflow-cpu 2.3.1`\n- `tensorflow-gpu 2.3.1`","depth":"sunlit","depthScore":33,"depthScoreParts":{"impact":32.5,"likelihood":0.2,"exploitation":0,"ransomware":0},"changes":[]}