CVE-2020-15202

mediumpriority · track · 36EPSS 0.013 · 70 %ileEUUS
grimoire priorityP3 · Track
Exploitable?
—
no known exploitation
Likely / severe?
1.29% (70th) EPSS
CVSS 6.8 · medium
Is it mine?
31 products
Check your exposure
Who says so?
4 sources
cnnvd · enisa_euvd · osv · nvd

EPSS · scored 2026-10-27

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.

01

cvss

Technical severity, 0–10. One row per scoring source.

9.0
010

base score 0–10 · higher = more severe · hover a vector to decode⚠ sources disagree · medium–critical · 6.8–9

v2.06.8mediumAV:N/AC:M/Au:N/C:P/I:P/A:Pprimary · NVD / NIST USexploitability 8.6 · impact 6.4
v3.19criticalCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:Hprimary · NVD / NIST USexploitability 2.2 · impact 6
v3.19criticalCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:Hsecondary · ENISA EU
v3.19criticalCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:Hsecondary · security-advisories@github.comexploitability 2.2 · impact 6
v3.19criticalCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:Hsecondary · OSV
v3.18.2highCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H/E:Usecondary · CVSS-BT (t0sche)
02

weaknesses

The CWE weakness classes this flaw belongs to.

CWE-197USCWE-197USCWE-754USCWE-754US
03

affected products (31)

Products and version ranges known to be affected.

showing 20 of 31
04

advisories (5)

Vendor and ecosystem advisories describing this.

  • GHSA-h6fg-mjxg-hqq4Integer truncation in Shard API usage2020-09-25ghsa · osvUS

    ### Impact The `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/util/work_sharder.h#L59-L60 However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/random_op.cc#L204-L205 https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/random_op.cc#L317-L318 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. ### Patches We have patched the issue in 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575. We will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by members of the Aivul Team from Qihoo 360.

  • BIT-tensorflow-2020-15202Integer truncation in Shard API usage2024-03-06vendor · osvUS

    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.

  • PYSEC-2020-1252020-09-25vendor · osvUS

    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.

  • PYSEC-2020-2822020-09-25vendor · osvUS

    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.

  • PYSEC-2020-3172020-09-25vendor · osvUS

    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.

05

also known as (11)

Other names and identifiers for this entity.

06

sources

Which sources assert this record, and when.

cnnvdenisa_euvdosvnvdNVDCVE.orgMITRE
published 2020-09-25modified 2026-06-17
07

references (21)

External citations — patches, advisories, analysis.

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