CVE-2021-29535

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedMul` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/87cf4d3ea9949051e50ca3f071fc909538a51cd0/tensorflow/core/kernels/quantized_mul_op.cc#L287-L290) assumes that the 4 arguments are always valid scalars and tries to access the numeric value directly. However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in 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.

CVSS v3 7.8 HIGH
CVSS v2.0 4.6 MEDIUM

7.8^/10

CVSS v3 : HIGH

Vector :

Exploitability : 1.8 / Impact : 5.9

Attack Vector LOCAL

Attack Complexity LOW

Privileges Required LOW

User Interaction NONE

Confidentiality Impact HIGH

Integrity Impact HIGH

Availability Impact HIGH

Scope UNCHANGED

4.6^/10

CVSS v2.0 : MEDIUM

Vector : AV:L/AC:L/Au:N/C:P/I:P/A:P

Exploitability : 3.9 / Impact : 6.4

Access Vector LOCAL

Access Complexity LOW

Authentication NONE

Confidentiality Impact PARTIAL

Integrity Impact PARTIAL

Availability Impact PARTIAL

References

Link	Resource
https://github.com/tensorflow/tensorflow/commit/efea03b38fb8d3b81762237dc85e579cc5fc6e87	Patch Third Party Advisory
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m3f9-w3p3-p669	Exploit Patch Third Party Advisory

Configurations

Configuration 1 (hide)

OR	cpe:2.3:a:google:tensorflow::::::::
	cpe:2.3:a:google:tensorflow::::::::
	cpe:2.3:a:google:tensorflow::::::::
	cpe:2.3:a:google:tensorflow::::::::

History

No history.

Information

Published : 2021-05-14 20:15

Updated : 2021-07-26 16:02

NVD link : CVE-2021-29535

Mitre link : CVE-2021-29535

CVE.ORG link : CVE-2021-29535

JSON object : View

Products Affected

google

tensorflow

CWE

CWE-787

Out-of-bounds Write

CWE-131

Incorrect Calculation of Buffer Size

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An attacker can cause a heap buffer overflow in `QuantizedMul` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/87cf4d3ea9949051e50ca3f071fc909538a51cd0/tensorflow/core/kernels/quantized_mul_op.cc#L287-L290) assumes that the 4 arguments are always valid scalars and tries to access the numeric value directly. However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in 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 c\u00f3digo abierto de extremo a extremo para el aprendizaje autom\u00e1tico. Un atacante puede causar un desbordamiento del b\u00fafer de la pila en la funci\u00f3n \"QuantizedMul\" al pasar umbrales no comprobados para la cuantificaci\u00f3n. Esto es debido a que la implementaci\u00f3n (https://github.com/tensorflow/tensorflow/blob/87cf4d3ea9949051e50ca3f071fc909538a51cd0/tensorflow/core/kernels/quantized_mul_op.cc#L287-L290) asume que los 4 argumentos son siempre escalares v\u00e1lidos e intenta acceder al valor num\u00e9rico directamente. Sin embargo, si alguno de estos tensores est\u00e1 vac\u00edo, entonces \".flat(T)()\" es un b\u00fafer vac\u00edo y acceder al elemento en una posici\u00f3n 0 resulta en un desbordamiento. La correcci\u00f3n ser\u00e1 incluida en TensorFlow versi\u00f3n 2.5.0. Tambi\u00e9n seleccionaremos este commit en TensorFlow versi\u00f3n 2.4.2, TensorFlow versi\u00f3n 2.3.3, TensorFlow versi\u00f3n 2.2.3 y TensorFlow versi\u00f3n 2.1.4, ya que estos tambi\u00e9n est\u00e1n afectados y a\u00fan est\u00e1n en el rango compatible"}], "lastModified": "2021-07-26T16:02:10.500", "configurations": [{"nodes": [{"negate": false, "cpeMatch": [{"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "vulnerable": true, "matchCriteriaId": "323ABCCE-24EB-47CC-87F6-48C101477587", "versionEndExcluding": "2.1.4"}, {"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "vulnerable": true, "matchCriteriaId": "64ABA90C-0649-4BB0-89C9-83C14BBDCC0F", "versionEndExcluding": "2.2.3", "versionStartIncluding": "2.2.0"}, {"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "vulnerable": true, "matchCriteriaId": "0F83E0CF-CBF6-4C24-8683-3E7A5DC95BA9", "versionEndExcluding": "2.3.3", "versionStartIncluding": "2.3.0"}, {"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "vulnerable": true, "matchCriteriaId": "8259531B-A8AC-4F8B-B60F-B69DE4767C03", "versionEndExcluding": "2.4.2", "versionStartIncluding": "2.4.0"}], "operator": "OR"}]}], "sourceIdentifier": "security-advisories@github.com"}