{"id":"CVE-2020-15208","aliases":["BIT-tensorflow-2020-15208","EUVD-2020-0204","GHSA-mxjj-953w-2c2v","PYSEC-2020-131","PYSEC-2020-288","PYSEC-2020-323","openSUSE-SU-2020:1766-1","openSUSE-SU-2024:12116-1"],"status":"published","title":"Data corruption in tensorflow-lite","description":"In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.","severity":{"version":"3.1","score":7.4,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N","level":"high","assessor":"cna","from":"cve"},"epss":{"day":"2026-11-10","score":0.00905,"percentile":0.60109,"model":"v2026.06.15"},"facts":{"in_kev":false,"known_exploited":false,"public_exploit":false,"fix_available":true},"cwes":["CWE-125","CWE-787"],"published":"2020-09-25T18:28:44Z","modified":"2026-10-20T14:10:49Z","fixes":[{"ecosystem":"PyPI","package":"tensorflow","fixed_in":["1.15.4","2.0.3","2.1.2","2.2.1","2.3.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-cpu","fixed_in":["1.15.4","2.0.3","2.1.2","2.2.1","2.3.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-gpu","fixed_in":["1.15.4","2.0.3","2.1.2","2.2.1","2.3.1"],"sources":["ghsa","osv"]},{"ecosystem":"Bitnami","package":"tensorflow","fixed_in":["1.15.4","2.0.3","2.1.2","2.2.1","2.3.1"],"sources":["osv"]}],"affected":[{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.15.4"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.0.0"},{"fixed":"2.0.3"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.1.0"},{"fixed":"2.1.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.2.0"},{"last_affected":"2.2.0"},{"fixed":"2.2.1"}]}],"versions":["2.2.0"]},{"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":"0"},{"fixed":"1.15.4"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.0.0"},{"fixed":"2.0.3"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.1.0"},{"fixed":"2.1.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.2.0"},{"last_affected":"2.2.0"},{"fixed":"2.2.1"}]}],"versions":["2.2.0"]},{"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":"0"},{"fixed":"1.15.4"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.0.0"},{"fixed":"2.0.3"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.1.0"},{"fixed":"2.1.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.2.0"},{"last_affected":"2.2.0"},{"fixed":"2.2.1"}]}],"versions":["2.2.0"]},{"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":"0"},{"fixed":"1.15.4"},{"introduced":"2.0.0"},{"fixed":"2.0.3"},{"introduced":"2.1.0"},{"fixed":"2.1.2"},{"introduced":"2.2.0"},{"fixed":"2.2.1"},{"introduced":"2.3.0"},{"fixed":"2.3.1"}]}]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.15.4"}]}],"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","1.2.0","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"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.0.0"},{"fixed":"2.0.3"}]}],"versions":["2.0.0","2.0.1","2.0.2"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.1.0"},{"fixed":"2.1.2"}]}],"versions":["2.1.0","2.1.1"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.2.0"},{"fixed":"2.2.1"}]}],"versions":["2.2.0"]},{"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":"0"},{"fixed":"1.15.4"}]}],"versions":["1.15.0"]},{"source":"osv","ecosystem":"PyP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Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mxjj-953w-2c2v","tags":["x_refsource_CONFIRM","x_transferred","Exploit","Third Party Advisory","advisory","evidence","web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/8ee24e7949a203d234489f9da2c5bf45a7d5157d","tags":["x_refsource_MISC","x_transferred","Patch","Third Party Advisory","advisory","fix","web"]},{"url":"http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html","tags":["vendor-advisory","x_refsource_SUSE","x_transferred","Mailing List","Third Party Advisory","advisory","web"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2020-15208","tags":["web","advisory"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-288.yaml","tags":["web"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-323.yaml","tags":["web"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-131.yaml","tags":["web"]},{"url":"https://github.com/advisories/GHSA-mxjj-953w-2c2v"},{"url":"https://github.com/tensorflow/tensorflow","tags":["package"]},{"url":"https://lists.opensuse.org/archives/list/security-announce@lists.opensuse.org/thread/TNMEEN772D6LWSHNB64QFB5TB3CZZEF4/","tags":["advisory"]},{"url":"https://bugzilla.suse.com/1173314","tags":["report"]},{"url":"https://bugzilla.suse.com/1175099","tags":["report"]},{"url":"https://bugzilla.suse.com/1175789","tags":["report"]},{"url":"https://bugzilla.suse.com/1177022","tags":["report"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15190","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15191","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15192","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15193","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15194","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15195","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15202","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15203","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15204","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15205","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15206","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15207","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15208","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15209","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15210","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15211","tags":["web"]},{"url":"","tags":["advisory"]},{"url":"https://www.suse.com/security/cve/CVE-2020-10531","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-26266","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-26270","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-22922","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-22923","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-22926","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37635","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37636","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37637","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37638","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37639","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37640","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37641","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37642","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37643","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37644","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37645","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37646","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37647","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37648","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37649","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37650","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37651","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37652","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37653","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37654","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37655","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37656","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37657","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37658","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37659","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37660","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37661","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37662","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37663","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37664","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37665","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37666","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37667","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37668","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37669","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37670","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37671","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37672","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37673","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37674","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37675","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37676","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37677","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37678","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37679","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37680","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37681","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37682","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37683","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37684","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37685","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37686","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37687","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37688","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37689","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37690","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37691","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37692","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41195","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41196","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41197","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41198","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41199","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41200","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41201","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41202","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41203","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41204","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41205","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41206","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41207","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41208","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41209","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41210","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41211","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41212","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41213","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41214","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41215","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41216","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41217","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41218","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41219","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41220","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41221","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41222","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41223","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41224","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41225","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41226","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41227","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41228","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21725","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21726","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21727","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21728","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21729","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21730","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21731","tags":["web"]},{"url":"https://www.suse.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corruption in tensorflow-lite","description":"In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.","status":"published","published":"2020-09-25T18:45:40Z","modified":"2024-08-04T13:08:22.832Z","cvss":[{"version":"3.1","score":7.4,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N","level":"high","assessor":"cna"}],"cwes":["CWE-125","CWE-787"],"updated_at":"2026-11-02T14:35:50.228781Z"}],"euvd":[{"id":"EUVD-2020-0204","description":"In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.","status":"published","published":"2020-09-25T18:45:40Z","modified":"2024-08-04T13:08:22Z","cvss":[{"version":"3.1","score":7.4,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N","level":"high"}],"updated_at":"2026-11-03T03:07:33.100327Z"}],"ghsa":[{"id":"GHSA-mxjj-953w-2c2v","title":"Data corruption in tensorflow-lite","description":"### Impact\nWhen determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes:\nhttps://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/types.h#L437-L442\n\nSince the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors.\n\n### Patches\nWe have patched the issue in 8ee24e7949a20 and will release patch releases for all versions between 1.15 and 2.3.\n\nWe recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 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 has been reported by members of the Aivul Team from Qihoo 360.","status":"published","published":"2020-09-25T18:28:44Z","modified":"2024-10-30T21:17:25Z","cvss":[{"version":"4.0","score":8.6,"vector":"CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N","level":"high"},{"version":"3.1","score":7.4,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N","level":"high"}],"cwes":["CWE-125","CWE-787"],"updated_at":"2026-11-02T14:38:14.769863Z"}],"nvd":[{"id":"CVE-2020-15208","description":"In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.","status":"published","published":"2020-09-25T19:15:16.103Z","modified":"2026-06-17T02:56:16.19Z","cvss":[{"version":"3.1","score":7.4,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N","level":"high","assessor":"secondary"},{"version":"3.1","score":9.8,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H","level":"critical","assessor":"primary"},{"version":"2.0","score":7.5,"vector":"AV:N/AC:L/Au:N/C:P/I:P/A:P","level":"high","assessor":"primary"}],"cwes":["CWE-125","CWE-787"],"updated_at":"2026-11-02T14:06:17.70091Z"}],"osv":[{"id":"CVE-2020-15208","description":"In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.","status":"published","published":"2020-09-25T19:15:16.103Z","modified":"2026-10-20T14:10:49.98500251Z","cvss":[{"version":"3.1","score":9.8,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H","level":"critical"}],"updated_at":"2026-11-02T15:44:14.828228Z"},{"id":"GHSA-mxjj-953w-2c2v","title":"Data corruption in tensorflow-lite","description":"### Impact\nWhen determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes:\nhttps://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/types.h#L437-L442\n\nSince the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors.\n\n### Patches\nWe have patched the issue in 8ee24e7949a20 and will release patch releases for all versions between 1.15 and 2.3.\n\nWe recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 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 has been reported by members of the Aivul Team from Qihoo 360.","status":"published","published":"2020-09-25T18:28:44Z","modified":"2026-07-08T06:00:53.820147724Z","cvss":[{"version":"3.1","score":7.4,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N","level":"high"},{"version":"4.0","score":8.6,"vector":"CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N","level":"high"}],"cwes":["CWE-125","CWE-787"],"updated_at":"2026-11-02T15:46:52.534897Z"},{"id":"BIT-tensorflow-2020-15208","title":"Data corruption in tensorflow-lite","description":"In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.","status":"published","published":"2024-03-06T11:20:29.898Z","modified":"2026-09-08T08:48:19.834537372Z","updated_at":"2026-11-02T15:28:35.51001Z"},{"id":"openSUSE-SU-2020:1766-1","title":"Security update for tensorflow2","description":"This update for tensorflow2 fixes the following issues:\n\n- updated to 2.1.2 with following fixes (boo#1177022):\n  * Fixes an undefined behavior causing a segfault in tf.raw_ops.Switch (CVE-2020-15190)\n  * Fixes three vulnerabilities in conversion to DLPack format (CVE-2020-15191, CVE-2020-15192, CVE-2020-15193)\n  * Fixes two vulnerabilities in SparseFillEmptyRowsGrad (CVE-2020-15194, CVE-2020-15195)\n  * Fixes an integer truncation vulnerability in code using the work sharder API (CVE-2020-15202)\n  * Fixes a format string vulnerability in tf.strings.as_string (CVE-2020-15203)\n  * Fixes segfault raised by calling session-only ops in eager mode (CVE-2020-15204)\n  * Fixes data leak and potential ASLR violation from tf.raw_ops.StringNGrams (CVE-2020-15205)\n  * Fixes segfaults caused by incomplete SavedModel validation (CVE-2020-15206)\n  * Fixes a data corruption due to a bug in negative indexing support in TFLite (CVE-2020-15207)\n  * Fixes a data corruption due to dimension mismatch in TFLite (CVE-2020-15208)\n  * Fixes several vulnerabilities in TFLite saved model format (CVE-2020-15209, CVE-2020-15210, CVE-2020-15211)\n","status":"published","published":"2020-10-29T11:23:39Z","modified":"2026-02-04T03:45:35.673536Z","updated_at":"2026-11-02T16:58:31.517538Z"},{"id":"openSUSE-SU-2024:12116-1","title":"tensorflow-lite-2.9.1-1.1 on GA media","description":"These are all security issues fixed in the tensorflow-lite-2.9.1-1.1 package on the GA media of openSUSE Tumbleweed.","status":"published","published":"2024-06-15T00:00:00Z","modified":"2026-02-04T03:04:19.609756Z","updated_at":"2026-11-02T16:58:35.485255Z"},{"id":"PYSEC-2020-131","description":"In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.","status":"published","published":"2020-09-25T19:15:00Z","modified":"2023-12-06T01:00:17.123611Z","updated_at":"2026-11-02T15:52:52.192131Z"},{"id":"PYSEC-2020-288","description":"In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.","status":"published","published":"2020-09-25T19:15:00Z","modified":"2023-12-06T01:00:17.123611Z","updated_at":"2026-11-02T15:52:52.682031Z"},{"id":"PYSEC-2020-323","description":"In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.","status":"published","published":"2020-09-25T19:15:00Z","modified":"2023-12-06T01:00:17.123611Z","updated_at":"2026-11-02T15:52:52.682031Z"}]}}