CVE-2020-26269
Heap out of bounds read in filesystem glob matching in TensorFlow
In TensorFlow release candidate versions 2.4.0rc*, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the parallel implementation of GetMatchingPaths but are not verified by the PRs introducing it (#40861 and #44310). Thus, we are completely rewriting the implementation to fully specify and validate these. This is patched in version 2.4.0. This issue only impacts master branch and the release candidates for TF version 2.4. The final release of the 2.4 release will be patched.
Attack profile
How easy it is to exploit
- Attack vector
- Network
- Complexity
- Low
- Privileges needed
- None
- User interaction
- None
What an attacker can affect
- Confidentiality
- None
- Integrity
- None
- Availability
- High
Exploit likelihood
What each source reports
NVD Score used
7.5
In TensorFlow release candidate versions 2.4.0rc*, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the parallel implementation of GetMatchingPaths but are not verified by the PRs introducing it (#40861 and #44310). Thus, we are completely rewriting the implementation to fully specify and validate these. This is patched in version 2.4.0. This issue only impacts master branch and the release candidates for TF version 2.4. The final release of the 2.4 release will be patched.
- Record
CVE-2020-26269- CVSS 3.1
- 7.5 High
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H - CVSS 2.0
- 5.0 Medium
AV:N/AC:L/Au:N/C:N/I:N/A:P - Weakness
- CWE-125
- Updated
- 2026-11-02
CVE List No score
Heap out of bounds read in filesystem glob matching in TensorFlow
In TensorFlow release candidate versions 2.4.0rc*, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the parallel implementation of GetMatchingPaths but are not verified by the PRs introducing it (#40861 and #44310). Thus, we are completely rewriting the implementation to fully specify and validate these. This is patched in version 2.4.0. This issue only impacts master branch and the release candidates for TF version 2.4. The final release of the 2.4 release will be patched.
- Record
CVE-2020-26269- Weakness
- CWE-125
- Updated
- 2026-11-02
EUVDEUVD-2020-0216 No score
In TensorFlow release candidate versions 2.4.0rc*, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the parallel implementation of GetMatchingPaths but are not verified by the PRs introducing it (#40861 and #44310). Thus, we are completely rewriting the implementation to fully specify and validate these. This is patched in version 2.4.0. This issue only impacts master branch and the release candidates for TF version 2.4. The final release of the 2.4 release will be patched.
- Record
EUVD-2020-0216- Updated
- 2026-11-03
GitHub AdvisoriesGHSA-9jjw-hf72-3mxw
7.2
TensorFlow vulnerable to heap out of bounds read in filesystem glob matching
Impact
The general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories:
if (!fs->Match(child_path, dirs[dir_index])) { ... }
Since dir_index is unconditionaly incremented outside of the lambda function where the vulnerable pattern occurs, this results in an access out of bounds issue under certain scenarios. For example, if /tmp/x is a directory that only contains a single file y, then the following scenario will cause a crash due to the out of bounds read:
>>> tf.io.gfile.glob('/tmp/x/')
Segmentation fault
There are multiple invariants and preconditions that are assumed by the parallel implementation of GetMatchingPaths but are not verified by the PRs introducing it (#40861 and #44310). Thus, we are completely rewriting the implementation to fully specify and validate these.
Patches
We have patched the issue in GitHub commit 8b5b9dc96666a3a5d27fad7179ff215e3b74b67c and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
This issue only impacts master branch and the release candidates for TF version 2.4. The final release of the 2.4 release will be patched.
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.
- Record
GHSA-9jjw-hf72-3mxw- CVSS 4.0
- 7.2 High
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:N/VA:H/SC:N/SI:N/SA:N - CVSS 3.1
- 9.1 Critical
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:H - Weakness
- CWE-125
- Updated
- 2026-11-02
OSV
7.5
In TensorFlow release candidate versions 2.4.0rc*, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the parallel implementation of GetMatchingPaths but are not verified by the PRs introducing it (#40861 and #44310). Thus, we are completely rewriting the implementation to fully specify and validate these. This is patched in version 2.4.0. This issue only impacts master branch and the release candidates for TF version 2.4. The final release of the 2.4 release will be patched.
- Record
CVE-2020-26269- CVSS 3.1
- 7.5 High
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H - Updated
- 2026-11-02
OSVGHSA-9jjw-hf72-3mxw
7.2
TensorFlow vulnerable to heap out of bounds read in filesystem glob matching
Impact
The general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories:
if (!fs->Match(child_path, dirs[dir_index])) { ... }
Since dir_index is unconditionaly incremented outside of the lambda function where the vulnerable pattern occurs, this results in an access out of bounds issue under certain scenarios. For example, if /tmp/x is a directory that only contains a single file y, then the following scenario will cause a crash due to the out of bounds read:
>>> tf.io.gfile.glob('/tmp/x/')
Segmentation fault
There are multiple invariants and preconditions that are assumed by the parallel implementation of GetMatchingPaths but are not verified by the PRs introducing it (#40861 and #44310). Thus, we are completely rewriting the implementation to fully specify and validate these.
Patches
We have patched the issue in GitHub commit 8b5b9dc96666a3a5d27fad7179ff215e3b74b67c and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
This issue only impacts master branch and the release candidates for TF version 2.4. The final release of the 2.4 release will be patched.
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.
- Record
GHSA-9jjw-hf72-3mxw- CVSS 4.0
- 7.2 High
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:N/VA:H/SC:N/SI:N/SA:N - CVSS 3.1
- 9.1 Critical
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:H - Weakness
- CWE-125
- Updated
- 2026-11-02
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OSVBIT-tensorflow-2020-26269 No score
Heap out of bounds read in filesystem glob matching in TensorFlow
In TensorFlow release candidate versions 2.4.0rc*, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the parallel implementation of GetMatchingPaths but are not verified by the PRs introducing it (#40861 and #44310). Thus, we are completely rewriting the implementation to fully specify and validate these. This is patched in version 2.4.0. This issue only impacts master branch and the release candidates for TF version 2.4. The final release of the 2.4 release will be patched.
- Record
BIT-tensorflow-2020-26269- Updated
- 2026-11-02
OSVPYSEC-2020-141 No score
In TensorFlow release candidate versions 2.4.0rc*, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the parallel implementation of GetMatchingPaths but are not verified by the PRs introducing it (#40861 and #44310). Thus, we are completely rewriting the implementation to fully specify and validate these. This is patched in version 2.4.0. This issue only impacts master branch and the release candidates for TF version 2.4. The final release of the 2.4 release will be patched.
- Record
PYSEC-2020-141- Updated
- 2026-11-02
OSVPYSEC-2020-300 No score
In TensorFlow release candidate versions 2.4.0rc*, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the parallel implementation of GetMatchingPaths but are not verified by the PRs introducing it (#40861 and #44310). Thus, we are completely rewriting the implementation to fully specify and validate these. This is patched in version 2.4.0. This issue only impacts master branch and the release candidates for TF version 2.4. The final release of the 2.4 release will be patched.
- Record
PYSEC-2020-300- Updated
- 2026-11-02
OSVPYSEC-2020-335 No score
In TensorFlow release candidate versions 2.4.0rc*, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the parallel implementation of GetMatchingPaths but are not verified by the PRs introducing it (#40861 and #44310). Thus, we are completely rewriting the implementation to fully specify and validate these. This is patched in version 2.4.0. This issue only impacts master branch and the release candidates for TF version 2.4. The final release of the 2.4 release will be patched.
- Record
PYSEC-2020-335- Updated
- 2026-11-02
Affected products
Affected packages
| Package | Affected | Fixed |
|---|---|---|
tensorflowPyPI |
2.4.0rc0 up to 2.4.0 | 2.4.0 |
tensorflow-cpuPyPI |
2.4.0rc0 up to 2.4.0 | 2.4.0 |
tensorflow-gpuPyPI |
2.4.0rc0 up to 2.4.0 | 2.4.0 |
tensorflowBitnami |
2.4.0-rc0 up to 2.4.0, 2.4.0-rc1 up to 2.4.0, 2.4.0-rc2 up to 2.4.0, 2.4.0-rc3 up to 2.4.0, 2.4.0-rc4 up to 2.4.0 | 2.4.0 |
tensorflowPyPI |
2.4.0rc0 up to 2.4.0, plus listed versions 2.4.0rc12.4.0rc22.4.0rc32.4.0rc4 |
2.4.0 |
History
| Recorded | Changed | Sources |
|---|---|---|
| facts | ||
| aliases | EUVD | |
| first indexed | CVE List, GitHub Advisories, NVD, OSV |
Dates are when Every CVE recorded each change. Upstream dates may differ.
In short
CVE-2020-26269 is a high vulnerability (CVSS 7.5) in Google Tensorflow, published December 10, 2020. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.70%, the 53rd percentile. Fixed in tensorflow 2.4.0.
References
github.com/tensorflow/tensorflow/security/advisories/GHSA-9jjw-hf72-3mxw
github.com/tensorflow/tensorflow/commit/8b5b9dc96666a3a5d27fad7179ff215e3b74b67c
nvd.nist.gov/vuln/detail/CVE-2020-26269
github.com/tensorflow/tensorflow/pull/40861
github.com/tensorflow/tensorflow/pull/44310
github.com/tensorflow/tensorflow/blob/458c6260265c46ebaf18052d6c61aea4b6b40926/tensorflow/core/platform/file_system_helper.cc
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github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-300.yaml
github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-335.yaml
github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-141.yaml
github.com/advisories/GHSA-9jjw-hf72-3mxw
github.com/tensorflow/tensorflow