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GitHub_MCVE-2020-26270

HistoryDec 10, 2020 - 11:15 p.m.

CVE-2020-26270

2020-12-1023:15:12

CWE-20

GitHub_M

web.nvd.nist.gov

cve-2020-26270

tensorflow

lstm

gru

input vulnerability

fix

nvd

denial of service

cuda backend

CVSS2

2.1

Attack Vector

LOCAL

Attack Complexity

LOW

Authentication

NONE

Confidentiality Impact

NONE

Integrity Impact

NONE

Availability Impact

PARTIAL

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

CVSS3

4.4

Attack Vector

LOCAL

Attack Complexity

LOW

Privileges Required

LOW

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

NONE

Integrity Impact

LOW

Availability Impact

LOW

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

AI Score

3.9

Confidence

High

EPSS

Percentile

12.6%

JSON

In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.

Affected configurations

Nvd

Vulners

Node

googletensorflowRange<1.15.5

googletensorflowRange2.0.0–2.0.4

googletensorflowRange2.1.0–2.1.3

googletensorflowRange2.2.0–2.2.2

googletensorflowRange2.3.0–2.3.2

VendorProductVersionCPE
googletensorflow*cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*

Vendor	Product	Version	CPE
google	tensorflow	*	cpe:2.3:a:google:tensorflow::::::::

CNA Affected

[
  {
    "product": "tensorflow",
    "vendor": "tensorflow",
    "versions": [
      {
        "status": "affected",
        "version": "< 1.15.5"
      },
      {
        "status": "affected",
        "version": ">= 2.0.0, < 2.0.4"
      },
      {
        "status": "affected",
        "version": ">= 2.1.0, < 2.1.3"
      },
      {
        "status": "affected",
        "version": ">= 2.2.0, < 2.2.2"
      },
      {
        "status": "affected",
        "version": ">= 2.3.0, < 2.3.2"
      }
    ]
  }
]