{"resultsPerPage":1,"startIndex":0,"totalResults":1,"format":"NVD_CVE","version":"2.0","timestamp":"2026-09-30T22:01:13.662","vulnerabilities":[{"cve":{"id":"CVE-2021-29529","sourceIdentifier":"security-advisories@github.com","published":"2021-05-14T20:15:11.937","lastModified":"2026-06-17T03:47:50.627","vulnStatus":"Modified","cveTags":[],"descriptions":[{"lang":"en","value":"TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a heap buffer overflow in `tf.raw_ops.QuantizedResizeBilinear` by manipulating input values so that float rounding results in off-by-one error in accessing image elements. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L62-L66) computes two integers (representing the upper and lower bounds for interpolation) by ceiling and flooring a floating point value. For some values of `in`, `interpolation->upper[i]` might be smaller than `interpolation->lower[i]`. This is an issue if `interpolation->upper[i]` is capped at `in_size-1` as it means that `interpolation->lower[i]` points outside of the image. Then, in the interpolation code(https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L245-L264), this would result in heap buffer overflow. 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 un desbordamiento del búfer de la pila en \"tf.raw_ops.QuantizedResizeBilinear\" al manipular los valores de entrada para que el redondeo flotante resulta en un error de uno en uno al acceder a los elementos de la imagen. Esto es debido a que la implementación (https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L62-L66) calcula dos números enteros (que representan los límites superior e inferior) por techo y piso un valor de punto flotante. Para algunos valores de \"in\",\" interpolation-)upper[i]\" podría ser menor que \"interpolation-)lower [i] \". Esto es un problema si \"interpolation-)upper[i]\" está limitado a \"in_size-1\" ya que significa que \"interpolation-)lower[i]\" apunta fuera de la imagen. Luego, en el código de interpolación (https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L245-L264), esto resultaría en un desbordamiento del búfer de la pila. La corrección será incluida en TensorFlow versión 2.5.0. También seleccionaremos este commit en TensorFlow versión 2.4.2, TensorFlow versión 2.3.3, TensorFlow versión 2.2.3 y TensorFlow versión 2.1.4, ya que estos también están afectados y aún están en el rango compatible"}],"affected":[{"source":"security-advisories@github.com","affectedData":[{"vendor":"tensorflow","product":"tensorflow","versions":[{"version":"< 2.1.4","status":"affected"},{"version":">= 2.2.0, < 2.2.3","status":"affected"},{"version":">= 2.3.0, < 2.3.3","status":"affected"},{"version":">= 2.4.0, < 2.4.2","status":"affected"}]}]}],"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:H/I:H/A:H","baseScore":7.8,"baseSeverity":"HIGH","attackVector":"LOCAL","attackComplexity":"LOW","privilegesRequired":"LOW","userInteraction":"NONE","scope":"UNCHANGED","confidentialityImpact":"HIGH","integrityImpact":"HIGH","availabilityImpact":"HIGH"},"exploitabilityScore":1.8,"impactScore":5.9}],"cvssMetricV2":[{"source":"nvd@nist.gov","type":"Primary","cvssData":{"version":"2.0","vectorString":"AV:L/AC:L/Au:N/C:P/I:P/A:P","baseScore":4.6,"accessVector":"LOCAL","accessComplexity":"LOW","authentication":"NONE","confidentialityImpact":"PARTIAL","integrityImpact":"PARTIAL","availabilityImpact":"PARTIAL"},"baseSeverity":"MEDIUM","exploitabilityScore":3.9,"impactScore":6.4,"acInsufInfo":false,"obtainAllPrivilege":false,"obtainUserPrivilege":false,"obtainOtherPrivilege":false,"userInteractionRequired":false}]},"weaknesses":[{"source":"security-advisories@github.com","type":"Secondary","description":[{"lang":"en","value":"CWE-131"}]},{"source":"nvd@nist.gov","type":"Primary","description":[{"lang":"en","value":"CWE-193"}]}],"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/f851613f8f0fb0c838d160ced13c134f778e3ce7","source":"security-advisories@github.com","tags":["Patch","Third Party Advisory"]},{"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jfp7-4j67-8r3q","source":"security-advisories@github.com","tags":["Exploit","Patch","Third Party Advisory"]},{"url":"https://github.com/tensorflow/tensorflow/commit/f851613f8f0fb0c838d160ced13c134f778e3ce7","source":"af854a3a-2127-422b-91ae-364da2661108","tags":["Patch","Third Party Advisory"]},{"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jfp7-4j67-8r3q","source":"af854a3a-2127-422b-91ae-364da2661108","tags":["Exploit","Patch","Third Party Advisory"]}]}}]}