CVE-2021-29549 Division by 0 in `QuantizedAdd`

2021-05-1419:10:41

CWE-369

GitHub_M

www.cve.org

2.5 Low

CVSS3

Attack Vector

LOCAL

Attack Complexity

HIGH

Privileges Required

LOW

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

NONE

Integrity Impact

NONE

Availability Impact

LOW

CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

0.0004 Low

EPSS

Percentile

12.8%

JSON

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in tf.raw_ops.QuantizedBatchNormWithGlobalNormalization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L289-L295) computes a modulo operation without validating that the divisor is not zero. Since vector_num_elements is determined based on input shapes(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L522-L544), a user can trigger scenarios where this quantity is 0. 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.

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"
      }
    ]
  }
]