CVE-2020-15208 Data corruption in tensorflow-lite

2020-09-2518:45:40

CWE-125

CWE-787

GitHub_M

www.cve.org

7.4 High

CVSS3

Attack Vector

NETWORK

Attack Complexity

HIGH

Privileges Required

NONE

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

HIGH

Integrity Impact

HIGH

Availability Impact

NONE

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

9.3 High

AI Score

Confidence

High

0.002 Low

EPSS

Percentile

53.6%

JSON

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a DCHECK which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

CNA Affected

[
  {
    "product": "tensorflow",
    "vendor": "tensorflow",
    "versions": [
      {
        "status": "affected",
        "version": "< 1.15.4"
      },
      {
        "status": "affected",
        "version": ">= 2.0.0, < 2.0.3"
      },
      {
        "status": "affected",
        "version": ">= 2.1.0, < 2.1.2"
      },
      {
        "status": "affected",
        "version": ">= 2.2.0, < 2.2.1"
      },
      {
        "status": "affected",
        "version": ">= 2.3.0, < 2.3.1"
      }
    ]
  }
]