CVEvulnerability

CVE-2020-15202

9.0 CRITICAL Published 2020-09-25 Modified 2026-06-17 Official page ↗
Status
Modified
Published
2020-09-25
Last modified
2026-06-17
Assigner
[email protected]
CVSS 3.1 ([email protected])
9.0 CRITICAL — CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
CVSS 3.1 ([email protected])
9.0 CRITICAL — CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
CVSS 2.0 ([email protected])
6.8 MEDIUM — AV:N/AC:M/Au:N/C:P/I:P/A:P
Weaknesses
CWE-197, CWE-754

Description

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments. However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used. In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption. The issue is patched in commits 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Affected configurations

• google tensorflow (< 1.15.4) • google tensorflow (>= 2.0.0 < 2.0.3) • google tensorflow (>= 2.1.0 < 2.1.2) • google tensorflow (>= 2.2.0 < 2.2.1) • google tensorflow (>= 2.3.0 < 2.3.1) • opensuse leap 15.2

Related

Weakness · CWE (2)

  • CWE-197 Numeric Truncation Error weakness
  • CWE-754 Improper Check for Unusual or Exceptional Conditions weakness

References