CVE-2021-29531
Vulnerability from cvelistv5
Published
2021-05-14 19:12
Modified
2024-08-03 22:11
Severity ?
EPSS score ?
Summary
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a `CHECK` fail in PNG encoding by providing an empty input tensor as the pixel data. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L57-L60) only validates that the total number of pixels in the image does not overflow. Thus, an attacker can send an empty matrix for encoding. However, if the tensor is empty, then the associated buffer is `nullptr`. Hence, when calling `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L79-L93), the first argument (i.e., `image.flat<T>().data()`) is `NULL`. This then triggers the `CHECK_NOTNULL` in the first line of `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/lib/png/png_io.cc#L345-L349). Since `image` is null, this results in `abort` being called after printing the stacktrace. Effectively, this allows an attacker to mount a denial of service attack. 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.
References
▼ | URL | Tags | |
---|---|---|---|
security-advisories@github.com | https://github.com/tensorflow/tensorflow/commit/26eb323554ffccd173e8a79a8c05c15b685ae4d1 | Patch, Third Party Advisory | |
security-advisories@github.com | https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3qxp-qjq7-w4hf | Exploit, Patch, Third Party Advisory | |
af854a3a-2127-422b-91ae-364da2661108 | https://github.com/tensorflow/tensorflow/commit/26eb323554ffccd173e8a79a8c05c15b685ae4d1 | Patch, Third Party Advisory | |
af854a3a-2127-422b-91ae-364da2661108 | https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3qxp-qjq7-w4hf | Exploit, Patch, Third Party Advisory |
Impacted products
Vendor | Product | Version | ||
---|---|---|---|---|
tensorflow | tensorflow |
Version: < 2.1.4 Version: >= 2.2.0, < 2.2.3 Version: >= 2.3.0, < 2.3.3 Version: >= 2.4.0, < 2.4.2 |
{ containers: { adp: [ { providerMetadata: { dateUpdated: "2024-08-03T22:11:05.385Z", orgId: "af854a3a-2127-422b-91ae-364da2661108", shortName: "CVE", }, references: [ { tags: [ "x_refsource_CONFIRM", "x_transferred", ], url: "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3qxp-qjq7-w4hf", }, { tags: [ "x_refsource_MISC", "x_transferred", ], url: "https://github.com/tensorflow/tensorflow/commit/26eb323554ffccd173e8a79a8c05c15b685ae4d1", }, ], title: "CVE Program Container", }, ], cna: { affected: [ { product: "tensorflow", vendor: "tensorflow", versions: [ { status: "affected", 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", }, ], }, ], descriptions: [ { lang: "en", value: "TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a `CHECK` fail in PNG encoding by providing an empty input tensor as the pixel data. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L57-L60) only validates that the total number of pixels in the image does not overflow. Thus, an attacker can send an empty matrix for encoding. However, if the tensor is empty, then the associated buffer is `nullptr`. Hence, when calling `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L79-L93), the first argument (i.e., `image.flat<T>().data()`) is `NULL`. This then triggers the `CHECK_NOTNULL` in the first line of `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/lib/png/png_io.cc#L345-L349). Since `image` is null, this results in `abort` being called after printing the stacktrace. Effectively, this allows an attacker to mount a denial of service attack. 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.", }, ], metrics: [ { cvssV3_1: { attackComplexity: "HIGH", attackVector: "LOCAL", availabilityImpact: "LOW", baseScore: 2.5, baseSeverity: "LOW", confidentialityImpact: "NONE", integrityImpact: "NONE", privilegesRequired: "LOW", scope: "UNCHANGED", userInteraction: "NONE", vectorString: "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L", version: "3.1", }, }, ], problemTypes: [ { descriptions: [ { cweId: "CWE-754", description: "CWE-754: Improper Check for Unusual or Exceptional Conditions", lang: "en", type: "CWE", }, ], }, ], providerMetadata: { dateUpdated: "2021-05-14T19:12:12", orgId: "a0819718-46f1-4df5-94e2-005712e83aaa", shortName: "GitHub_M", }, references: [ { tags: [ "x_refsource_CONFIRM", ], url: "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3qxp-qjq7-w4hf", }, { tags: [ "x_refsource_MISC", ], url: "https://github.com/tensorflow/tensorflow/commit/26eb323554ffccd173e8a79a8c05c15b685ae4d1", }, ], source: { advisory: "GHSA-3qxp-qjq7-w4hf", discovery: "UNKNOWN", }, title: "CHECK-fail in tf.raw_ops.EncodePng", x_legacyV4Record: { CVE_data_meta: { ASSIGNER: "security-advisories@github.com", ID: "CVE-2021-29531", STATE: "PUBLIC", TITLE: "CHECK-fail in tf.raw_ops.EncodePng", }, affects: { vendor: { vendor_data: [ { product: { product_data: [ { product_name: "tensorflow", version: { version_data: [ { version_value: "< 2.1.4", }, { version_value: ">= 2.2.0, < 2.2.3", }, { version_value: ">= 2.3.0, < 2.3.3", }, { version_value: ">= 2.4.0, < 2.4.2", }, ], }, }, ], }, vendor_name: "tensorflow", }, ], }, }, data_format: "MITRE", data_type: "CVE", data_version: "4.0", description: { description_data: [ { lang: "eng", value: "TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a `CHECK` fail in PNG encoding by providing an empty input tensor as the pixel data. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L57-L60) only validates that the total number of pixels in the image does not overflow. Thus, an attacker can send an empty matrix for encoding. However, if the tensor is empty, then the associated buffer is `nullptr`. Hence, when calling `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L79-L93), the first argument (i.e., `image.flat<T>().data()`) is `NULL`. This then triggers the `CHECK_NOTNULL` in the first line of `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/lib/png/png_io.cc#L345-L349). Since `image` is null, this results in `abort` being called after printing the stacktrace. Effectively, this allows an attacker to mount a denial of service attack. 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.", }, ], }, impact: { cvss: { attackComplexity: "HIGH", attackVector: "LOCAL", availabilityImpact: "LOW", baseScore: 2.5, baseSeverity: "LOW", confidentialityImpact: "NONE", integrityImpact: "NONE", privilegesRequired: "LOW", scope: "UNCHANGED", userInteraction: "NONE", vectorString: "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L", version: "3.1", }, }, problemtype: { problemtype_data: [ { description: [ { lang: "eng", value: "CWE-754: Improper Check for Unusual or Exceptional Conditions", }, ], }, ], }, references: { reference_data: [ { name: "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3qxp-qjq7-w4hf", refsource: "CONFIRM", url: "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3qxp-qjq7-w4hf", }, { name: "https://github.com/tensorflow/tensorflow/commit/26eb323554ffccd173e8a79a8c05c15b685ae4d1", refsource: "MISC", url: "https://github.com/tensorflow/tensorflow/commit/26eb323554ffccd173e8a79a8c05c15b685ae4d1", }, ], }, source: { advisory: "GHSA-3qxp-qjq7-w4hf", discovery: "UNKNOWN", }, }, }, }, cveMetadata: { assignerOrgId: "a0819718-46f1-4df5-94e2-005712e83aaa", assignerShortName: "GitHub_M", cveId: "CVE-2021-29531", datePublished: "2021-05-14T19:12:12", dateReserved: "2021-03-30T00:00:00", dateUpdated: "2024-08-03T22:11:05.385Z", state: "PUBLISHED", }, dataType: "CVE_RECORD", dataVersion: "5.1", "vulnerability-lookup:meta": { nvd: "{\"cve\":{\"id\":\"CVE-2021-29531\",\"sourceIdentifier\":\"security-advisories@github.com\",\"published\":\"2021-05-14T20:15:12.027\",\"lastModified\":\"2024-11-21T06:01:19.327\",\"vulnStatus\":\"Modified\",\"cveTags\":[],\"descriptions\":[{\"lang\":\"en\",\"value\":\"TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a `CHECK` fail in PNG encoding by providing an empty input tensor as the pixel data. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L57-L60) only validates that the total number of pixels in the image does not overflow. Thus, an attacker can send an empty matrix for encoding. However, if the tensor is empty, then the associated buffer is `nullptr`. Hence, when calling `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L79-L93), the first argument (i.e., `image.flat<T>().data()`) is `NULL`. This then triggers the `CHECK_NOTNULL` in the first line of `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/lib/png/png_io.cc#L345-L349). Since `image` is null, this results in `abort` being called after printing the stacktrace. Effectively, this allows an attacker to mount a denial of service attack. 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 \\\"CHECK\\\" en una codificación PNG al proporcionar un tensor de entrada vacío como datos de píxeles. Esto es debido a que la implementación (https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L57-L60) solo comprueba que el número total de píxeles en una imagen no se desborda. Por lo tanto, un atacante puede enviar una matriz vacía para codificar. Sin embargo, si el tensor está vacío, entonces el búfer asociado es \\\"nullptr\\\". Por lo tanto, al llamar a la función \\\"png::WriteImageToBuffer\\\" (https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L79-L93), el primer argumento (es decir, \\\"image.flat (T) () .data ()\\\") es \\\"NULL\\\". Esto luego desencadena el \\\"CHECK_NOTNULL\\\" en una primera línea de la función \\\"png::WriteImageToBuffer\\\" (https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/lib/png/png_45-Lcc349L). Dado que \\\"image\\\" es null, esto resulta en que se llame a \\\"abort\\\" después de imprimir el stacktrace. Efectivamente, esto permite a un atacante montar un ataque de denegación de servicio. 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 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Sightings
Author | Source | Type | Date |
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Nomenclature
- Seen: The vulnerability was mentioned, discussed, or seen somewhere by the user.
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