{"id":"CVE-2020-15198","aliases":["BIT-tensorflow-2020-15198","EUVD-2020-0194","GHSA-jc87-6vpp-7ff3","PYSEC-2020-121","PYSEC-2020-278","PYSEC-2020-313"],"status":"published","title":"Heap buffer overflow in Tensorflow","description":"In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.","severity":{"version":"3.1","score":5.4,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N","level":"medium","assessor":"cna","from":"cve"},"epss":{"day":"2026-11-11","score":0.00542,"percentile":0.45996,"model":"v2026.06.15"},"facts":{"in_kev":false,"known_exploited":false,"public_exploit":false,"fix_available":true},"cwes":["CWE-119","CWE-122"],"published":"2020-09-25T18:28:22Z","modified":"2026-10-20T14:10:31Z","fixes":[{"ecosystem":"PyPI","package":"tensorflow","fixed_in":["2.3.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-cpu","fixed_in":["2.3.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-gpu","fixed_in":["2.3.1"],"sources":["ghsa","osv"]},{"ecosystem":"Bitnami","package":"tensorflow","fixed_in":["2.3.1"],"sources":["osv"]}],"affected":[{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.3.0"},{"last_affected":"2.3.0"},{"fixed":"2.3.1"}]}],"versions":["2.3.0"]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.3.0"},{"last_affected":"2.3.0"},{"fixed":"2.3.1"}]}],"versions":["2.3.0"]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.3.0"},{"last_affected":"2.3.0"},{"fixed":"2.3.1"}]}],"versions":["2.3.0"]},{"source":"osv","ecosystem":"Bitnami","package":"tensorflow","ranges":[{"type":"SEMVER","events":[{"introduced":"2.3.0"},{"fixed":"2.3.1"}]}]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.3.0"},{"fixed":"2.3.1"}]}],"versions":["2.3.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.3.0"},{"fixed":"2.3.1"}]}],"versions":["2.3.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.3.0"},{"fixed":"2.3.1"}]}],"versions":["2.3.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"GIT","events":[{"introduced":"0"},{"fixed":"3cbb917b4714766030b28eba9fb41bb97ce9ee02"}]},{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.3.1"}]}],"versions":["0.12.0rc0","0.12.0rc1","0.12.0","0.12.1","1.0.0","1.0.1","1.1.0rc0","1.1.0rc1","1.1.0rc2","1.1.0","1.2.0rc0","1.2.0rc1","1.2.0rc2","1.2.0","1.2.1","1.3.0rc0","1.3.0rc1","1.3.0rc2","1.3.0","1.4.0rc0","1.4.0rc1","1.4.0","1.4.1","1.5.0rc0","1.5.0rc1","1.5.0","1.5.1","1.6.0rc0","1.6.0rc1","1.6.0","1.7.0rc0","1.7.0rc1","1.7.0","1.7.1","1.8.0rc0","1.8.0rc1","1.8.0","1.9.0rc0","1.9.0rc1","1.9.0rc2","1.9.0","1.10.0rc0","1.10.0rc1","1.10.0","1.10.1","1.11.0rc0","1.11.0rc1","1.11.0rc2","1.11.0","1.12.0rc0","1.12.0rc1","1.12.0rc2","1.12.0","1.12.2","1.12.3","1.13.0rc0","1.13.0rc1","1.13.0rc2","1.13.1","1.13.2","1.14.0rc0","1.14.0rc1","1.14.0","1.15.0rc0","1.15.0rc1","1.15.0rc2","1.15.0rc3","1.15.0","1.15.2","1.15.3","1.15.4","1.15.5","2.0.0a0","2.0.0b0","2.0.0b1","2.0.0rc0","2.0.0rc1","2.0.0rc2","2.0.0","2.0.1","2.0.2","2.0.3","2.0.4","2.1.0rc0","2.1.0rc1","2.1.0rc2","2.1.0","2.1.1","2.1.2","2.1.3","2.2.0rc0","2.2.0rc1","2.2.0rc2","2.2.0rc3","2.2.0rc4","2.2.0","2.2.1","2.2.2","2.3.0rc0","2.3.0rc1","2.3.0rc2","2.3.0","2.1.4","2.2.3"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"GIT","events":[{"introduced":"0"},{"fixed":"3cbb917b4714766030b28eba9fb41bb97ce9ee02"}]},{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.3.1"}]}],"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"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"GIT","events":[{"introduced":"0"},{"fixed":"3cbb917b4714766030b28eba9fb41bb97ce9ee02"}]},{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.3.1"}]}],"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"]}],"products":[{"vendor":"google","product":"tensorflow"},{"vendor":"tensorflow","product":"tensorflow"}],"references":[{"url":"https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1","tags":["x_refsource_MISC","x_transferred","Third Party Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02","tags":["x_refsource_MISC","x_transferred","Patch","Third Party Advisory","advisory","fix","web"]},{"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jc87-6vpp-7ff3","tags":["x_refsource_CONFIRM","x_transferred","Exploit","Third Party Advisory","advisory","evidence","web"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2020-15198","tags":["web","advisory"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-278.yaml","tags":["web"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-313.yaml","tags":["web"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-121.yaml","tags":["web"]},{"url":"https://github.com/advisories/GHSA-jc87-6vpp-7ff3"},{"url":"https://github.com/tensorflow/tensorflow","tags":["package"]}],"sources":{"cve":[{"id":"CVE-2020-15198","title":"Heap buffer overflow in Tensorflow","description":"In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.","status":"published","published":"2020-09-25T18:40:25Z","modified":"2024-08-04T13:08:22.711Z","cvss":[{"version":"3.1","score":5.4,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N","level":"medium","assessor":"cna"}],"cwes":["CWE-122","CWE-119"],"updated_at":"2026-11-02T14:35:50.545879Z"}],"euvd":[{"id":"EUVD-2020-0194","description":"In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.","status":"published","published":"2020-09-25T18:40:25Z","modified":"2024-08-04T13:08:22Z","cvss":[{"version":"3.1","score":5.4,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N","level":"medium"}],"updated_at":"2026-11-03T03:07:33.100327Z"}],"ghsa":[{"id":"GHSA-jc87-6vpp-7ff3","title":"Heap buffer overflow in Tensorflow","description":"### Impact\nThe `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel:\nhttps://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L193-L195\n\nThus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers.\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)","status":"published","published":"2020-09-25T18:28:22Z","modified":"2024-10-28T19:58:01Z","cvss":[{"version":"4.0","score":6.3,"vector":"CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:N/SC:L/SI:L/SA:N","level":"medium"},{"version":"3.1","score":5.4,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N","level":"medium"}],"cwes":["CWE-119","CWE-122"],"updated_at":"2026-11-02T14:38:14.769863Z"}],"nvd":[{"id":"CVE-2020-15198","description":"In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.","status":"published","published":"2020-09-25T19:15:15.057Z","modified":"2026-06-17T02:56:14.857Z","cvss":[{"version":"3.1","score":5.4,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N","level":"medium","assessor":"secondary"},{"version":"3.1","score":5.4,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N","level":"medium","assessor":"primary"},{"version":"2.0","score":5.8,"vector":"AV:N/AC:M/Au:N/C:P/I:P/A:N","level":"medium","assessor":"primary"}],"cwes":["CWE-119","CWE-122"],"updated_at":"2026-11-02T14:06:17.70091Z"}],"osv":[{"id":"CVE-2020-15198","description":"In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.","status":"published","published":"2020-09-25T19:15:15.057Z","modified":"2026-10-20T14:10:31.875869566Z","cvss":[{"version":"3.1","score":5.4,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N","level":"medium"}],"updated_at":"2026-11-02T15:44:14.828228Z"},{"id":"GHSA-jc87-6vpp-7ff3","title":"Heap buffer overflow in Tensorflow","description":"### Impact\nThe `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel:\nhttps://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L193-L195\n\nThus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers.\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)","status":"published","published":"2020-09-25T18:28:22Z","modified":"2026-09-10T03:49:25.846176475Z","cvss":[{"version":"3.1","score":5.4,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N","level":"medium"},{"version":"4.0","score":6.3,"vector":"CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:N/SC:L/SI:L/SA:N","level":"medium"}],"cwes":["CWE-119","CWE-122"],"updated_at":"2026-11-02T15:46:50.336262Z"},{"id":"BIT-tensorflow-2020-15198","title":"Heap buffer overflow in Tensorflow","description":"In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.","status":"published","published":"2024-03-06T11:20:42.418Z","modified":"2026-09-08T08:48:19.877604724Z","updated_at":"2026-11-02T15:28:35.51001Z"},{"id":"PYSEC-2020-121","description":"In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.","status":"published","published":"2020-09-25T19:15:00Z","modified":"2023-12-06T01:00:16.515389Z","updated_at":"2026-11-02T15:52:52.192131Z"},{"id":"PYSEC-2020-278","description":"In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.","status":"published","published":"2020-09-25T19:15:00Z","modified":"2023-12-06T01:00:16.515389Z","updated_at":"2026-11-02T15:52:52.682031Z"},{"id":"PYSEC-2020-313","description":"In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.","status":"published","published":"2020-09-25T19:15:00Z","modified":"2023-12-06T01:00:16.515389Z","updated_at":"2026-11-02T15:52:52.682031Z"}]}}