{"id":"CVE-2020-15210","aliases":["BIT-tensorflow-2020-15210","EUVD-2020-0206","GHSA-x9j7-x98r-r4w2","PYSEC-2020-133","PYSEC-2020-290","PYSEC-2020-325","openSUSE-SU-2020:1766-1"],"status":"published","title":"Segmentation fault 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, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.","severity":{"version":"3.1","score":6.5,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:H","level":"medium","assessor":"cna","from":"cve"},"epss":{"day":"2026-11-09","score":0.00739,"percentile":0.54838,"model":"v2026.06.15"},"facts":{"in_kev":false,"known_exploited":false,"public_exploit":false,"fix_available":true},"cwes":["CWE-20","CWE-787"],"published":"2020-09-25T18:28:51Z","modified":"2026-10-20T14:10:58Z","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-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-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":"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":"Py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Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x9j7-x98r-r4w2","tags":["x_refsource_CONFIRM","x_transferred","Exploit","Third Party Advisory","advisory","evidence","web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/d58c96946b2880991d63d1dacacb32f0a4dfa453","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-2020-15210","tags":["web","advisory"]},{"url":"https://github.com/tensorflow/tensorflow/commit/094329d0dcb8290bed2b1ee420934971f422c86d","tags":["web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/1c8709b437fec10875b0cf271889afec9bbf582e","tags":["web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/8c2092e9f9ef78b3f9060f8bf5ce7a49d1ccdc8f","tags":["web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/f4159ccef23d11eb58ee4263beaaeac1be3343c7","tags":["web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/f50a14b00560a383865c2273e4a9094add3888d5","tags":["web"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-290.yaml","tags":["web"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-325.yaml","tags":["web"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-133.yaml","tags":["web"]},{"url":"https://github.com/advisories/GHSA-x9j7-x98r-r4w2"},{"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"]}],"sources":{"cve":[{"id":"CVE-2020-15210","title":"Segmentation fault 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, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.","status":"published","published":"2020-09-25T18:45:30Z","modified":"2024-08-04T13:08:22.871Z","cvss":[{"version":"3.1","score":6.5,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:H","level":"medium","assessor":"cna"}],"cwes":["CWE-20"],"updated_at":"2026-11-02T14:35:50.228781Z"}],"euvd":[{"id":"EUVD-2020-0206","description":"In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.","status":"published","published":"2020-09-25T18:45:30Z","modified":"2024-08-04T13:08:22Z","cvss":[{"version":"3.1","score":6.5,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:H","level":"medium"}],"updated_at":"2026-11-03T03:07:33.100327Z"}],"ghsa":[{"id":"GHSA-x9j7-x98r-r4w2","title":"Segmentation fault in tensorflow-lite","description":"### Impact\nIf a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption.\n\n### Patches\nWe have patched the issue in d58c96946b 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### Workarounds\nA potential workaround would be to add a custom `Verifier` to the model loading code to ensure that no operator reuses tensors as both inputs and outputs. Care should be taken to check all types of inputs (i.e., constant or variable tensors as well as optional tensors).\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 discovered from a variant analysis of [GHSA-cvpc-8phh-8f45](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cvpc-8phh-8f45).","status":"published","published":"2020-09-25T18:28:51Z","modified":"2024-10-28T14:55:41Z","cvss":[{"version":"4.0","score":8.3,"vector":"CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:L/VA:H/SC:N/SI:N/SA:N","level":"high"},{"version":"3.1","score":6.5,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:H","level":"medium"}],"cwes":["CWE-20","CWE-787"],"updated_at":"2026-11-02T14:38:14.769863Z"}],"nvd":[{"id":"CVE-2020-15210","description":"In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.","status":"published","published":"2020-09-25T19:15:16.307Z","modified":"2026-06-17T02:56:16.467Z","cvss":[{"version":"3.1","score":6.5,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:H","level":"medium","assessor":"secondary"},{"version":"3.1","score":6.5,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:H","level":"medium","assessor":"primary"},{"version":"2.0","score":5.8,"vector":"AV:N/AC:M/Au:N/C:N/I:P/A:P","level":"medium","assessor":"primary"}],"cwes":["CWE-20","CWE-787"],"updated_at":"2026-11-02T14:06:17.70091Z"}],"osv":[{"id":"CVE-2020-15210","description":"In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.","status":"published","published":"2020-09-25T19:15:16.307Z","modified":"2026-10-20T14:10:58.606941171Z","cvss":[{"version":"3.1","score":6.5,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:H","level":"medium"}],"updated_at":"2026-11-02T15:44:14.828228Z"},{"id":"GHSA-x9j7-x98r-r4w2","title":"Segmentation fault in tensorflow-lite","description":"### Impact\nIf a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption.\n\n### Patches\nWe have patched the issue in d58c96946b 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### Workarounds\nA potential workaround would be to add a custom `Verifier` to the model loading code to ensure that no operator reuses tensors as both inputs and outputs. Care should be taken to check all types of inputs (i.e., constant or variable tensors as well as optional tensors).\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 discovered from a variant analysis of [GHSA-cvpc-8phh-8f45](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cvpc-8phh-8f45).","status":"published","published":"2020-09-25T18:28:51Z","modified":"2026-07-08T06:28:20.393272193Z","cvss":[{"version":"3.1","score":6.5,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:H","level":"medium"},{"version":"4.0","score":8.3,"vector":"CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:L/VA:H/SC:N/SI:N/SA:N","level":"high"}],"cwes":["CWE-20","CWE-787"],"updated_at":"2026-11-02T15:46:59.835583Z"},{"id":"BIT-tensorflow-2020-15210","title":"Segmentation fault 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, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.","status":"published","published":"2024-03-06T11:20:27.42Z","modified":"2026-09-08T08:48:19.885339836Z","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":"PYSEC-2020-133","description":"In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 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":"2023-12-06T01:00:17.243369Z","updated_at":"2026-11-02T15:52:52.192131Z"},{"id":"PYSEC-2020-290","description":"In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 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":"2023-12-06T01:00:17.243369Z","updated_at":"2026-11-02T15:52:52.682031Z"},{"id":"PYSEC-2020-325","description":"In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 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":"2023-12-06T01:00:17.243369Z","updated_at":"2026-11-02T15:52:52.682031Z"}]}}