{"resultsPerPage":1,"startIndex":0,"totalResults":1,"format":"NVD_CVE","version":"2.0","timestamp":"2026-05-02T16:18:33.548","vulnerabilities":[{"cve":{"id":"CVE-2021-29533","sourceIdentifier":"security-advisories@github.com","published":"2021-05-14T20:15:12.120","lastModified":"2024-11-21T06:01:19.577","vulnStatus":"Modified","cveTags":[],"descriptions":[{"lang":"en","value":"TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK` failure by passing an empty image to `tf.raw_ops.DrawBoundingBoxes`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/ea34a18dc3f5c8d80a40ccca1404f343b5d55f91/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L148-L165) uses `CHECK_*` assertions instead of `OP_REQUIRES` to validate user controlled inputs. Whereas `OP_REQUIRES` allows returning an error condition back to the user, the `CHECK_*` macros result in a crash if the condition is false, similar to `assert`. In this case, `height` is 0 from the `images` input. This results in `max_box_row_clamp` being negative and the assertion being falsified, followed by aborting program execution. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range."},{"lang":"es","value":"TensorFlow es una plataforma de código abierto de extremo a extremo para el aprendizaje automático. Un atacante puede desencadenar una denegación de servicio por medio de un fallo de \"CHECK\" al pasar una imagen vacía a \"tf.raw_ops.DrawBoundingBoxes\". Esto es debido a que la implementación (https://github.com/tensorflow/tensorflow/blob/ea34a18dc3f5c8d80a40ccca1404f343b5d55f91/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L148-L165) usa \"CHECIRES_ * para\" comprobar las entradas controladas por el usuario. Mientras que \"OP_REQUIRES\" permite devolver una condición de error al usuario, las macros\" CHECK_ * \"dan como resultado un bloqueo si la condición es falsa, similar a\" assert\". En este caso, \"height\" es 0 de la entrada de \"images\". Esto resulta en que \"max_box_row_clamp\" sea negativo y la aserción se falsifique, seguido de la interrupción de una ejecución del programa. La corrección será incluída en TensorFlow versión 2.5.0"}],"metrics":{"cvssMetricV31":[{"source":"security-advisories@github.com","type":"Secondary","cvssData":{"version":"3.1","vectorString":"CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L","baseScore":2.5,"baseSeverity":"LOW","attackVector":"LOCAL","attackComplexity":"HIGH","privilegesRequired":"LOW","userInteraction":"NONE","scope":"UNCHANGED","confidentialityImpact":"NONE","integrityImpact":"NONE","availabilityImpact":"LOW"},"exploitabilityScore":1.0,"impactScore":1.4},{"source":"nvd@nist.gov","type":"Primary","cvssData":{"version":"3.1","vectorString":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","baseScore":5.5,"baseSeverity":"MEDIUM","attackVector":"LOCAL","attackComplexity":"LOW","privilegesRequired":"LOW","userInteraction":"NONE","scope":"UNCHANGED","confidentialityImpact":"NONE","integrityImpact":"NONE","availabilityImpact":"HIGH"},"exploitabilityScore":1.8,"impactScore":3.6}],"cvssMetricV2":[{"source":"nvd@nist.gov","type":"Primary","cvssData":{"version":"2.0","vectorString":"AV:L/AC:L/Au:N/C:N/I:N/A:P","baseScore":2.1,"accessVector":"LOCAL","accessComplexity":"LOW","authentication":"NONE","confidentialityImpact":"NONE","integrityImpact":"NONE","availabilityImpact":"PARTIAL"},"baseSeverity":"LOW","exploitabilityScore":3.9,"impactScore":2.9,"acInsufInfo":false,"obtainAllPrivilege":false,"obtainUserPrivilege":false,"obtainOtherPrivilege":false,"userInteractionRequired":false}]},"weaknesses":[{"source":"security-advisories@github.com","type":"Secondary","description":[{"lang":"en","value":"CWE-754"}]}],"configurations":[{"nodes":[{"operator":"OR","negate":false,"cpeMatch":[{"vulnerable":true,"criteria":"cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*","versionEndExcluding":"2.1.4","matchCriteriaId":"323ABCCE-24EB-47CC-87F6-48C101477587"},{"vulnerable":true,"criteria":"cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*","versionStartIncluding":"2.2.0","versionEndExcluding":"2.2.3","matchCriteriaId":"64ABA90C-0649-4BB0-89C9-83C14BBDCC0F"},{"vulnerable":true,"criteria":"cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*","versionStartIncluding":"2.3.0","versionEndExcluding":"2.3.3","matchCriteriaId":"0F83E0CF-CBF6-4C24-8683-3E7A5DC95BA9"},{"vulnerable":true,"criteria":"cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*","versionStartIncluding":"2.4.0","versionEndExcluding":"2.4.2","matchCriteriaId":"8259531B-A8AC-4F8B-B60F-B69DE4767C03"}]}]}],"references":[{"url":"https://github.com/tensorflow/tensorflow/commit/b432a38fe0e1b4b904a6c222cbce794c39703e87","source":"security-advisories@github.com","tags":["Patch","Third Party Advisory"]},{"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-393f-2jr3-cp69","source":"security-advisories@github.com","tags":["Exploit","Patch","Third Party Advisory"]},{"url":"https://github.com/tensorflow/tensorflow/commit/b432a38fe0e1b4b904a6c222cbce794c39703e87","source":"af854a3a-2127-422b-91ae-364da2661108","tags":["Patch","Third Party Advisory"]},{"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-393f-2jr3-cp69","source":"af854a3a-2127-422b-91ae-364da2661108","tags":["Exploit","Patch","Third Party Advisory"]}]}}]}