CVE-2021-29591: Tensorflow Stack Overflow Due To Looping Vulnerability

HIGH
Advisory Identifier: GHSA-cwv3-863g-39vx
Share
CVSS 7.3
CWE-835 CWE-674
Published
Advisory Summary

CVE-2021-29591 is a HIGH (CVSS 7.3) stack overflow due to looping vulnerability (CWE-835: Loop with Unreachable Exit Condition ('Infinite Loop')) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves stack overflow due to looping tflite subgraph. Remediation is available by upgrading affected packages to version 2.1.4, 2.2.3, 2.3.3, 2.4.2.

CVE-2021-29591 at a Glance

CVE Identifier CVE-2021-29591
GHSA Identifier GHSA-cwv3-863g-39vx
Severity HIGH
CVSS v3.1 Base Score 7.3
CWE Classification CWE-835: Loop with Unreachable Exit Condition ('Infinite Loop')
Affected Product Tensorflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 7.3

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H).

Attack Vector Local (AV:L)
Attack Complexity Low (AC:L)
Privileges Required Low (PR:L)
User Interaction None (UI:N)
Scope Unchanged (S:U)
Confidentiality High (C:H)
Integrity Low (I:L)
Availability High (A:H)

How to Fix CVE-2021-29591

To remediate this vulnerability, upgrade all affected Tensorflow dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

tensorflow fixed: 2.1.4 
pip install tensorflow>=2.1.4
tensorflow fixed: 2.2.3 
pip install tensorflow>=2.2.3
tensorflow fixed: 2.3.3 
pip install tensorflow>=2.3.3
tensorflow fixed: 2.4.2 
pip install tensorflow>=2.4.2
tensorflow-cpu fixed: 2.1.4 
pip install tensorflow-cpu>=2.1.4
tensorflow-cpu fixed: 2.2.3 
pip install tensorflow-cpu>=2.2.3
tensorflow-cpu fixed: 2.3.3 
pip install tensorflow-cpu>=2.3.3
tensorflow-cpu fixed: 2.4.2 
pip install tensorflow-cpu>=2.4.2
tensorflow-gpu fixed: 2.1.4 
pip install tensorflow-gpu>=2.1.4
tensorflow-gpu fixed: 2.2.3 
pip install tensorflow-gpu>=2.2.3
tensorflow-gpu fixed: 2.3.3 
pip install tensorflow-gpu>=2.3.3
tensorflow-gpu fixed: 2.4.2 
pip install tensorflow-gpu>=2.4.2
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release: 

pip show tensorflow

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2021-29591, inspect your installed packages using pip:

pip show tensorflow

Analyze the terminal output to locate any version of Tensorflow in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 2.1.4), your application is affected.

Note: The pip show tensorflow command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-835: Loop with Unreachable Exit Condition ('Infinite Loop'), where the product contains an iteration or loop with an exit condition that cannot be reached, i.e., an infinite loop. In Tensorflow, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

### Impact TFlite graphs must not have loops between nodes. However, this condition was not checked and an attacker could craft models that would result in infinite loop during evaluation. In certain cases, the infinite loop would be replaced by stack overflow due to too many recursive calls. For example, the [`While` implementation](https://github.com/tensorflow/tensorflow/blob/106d8f4fb89335a2c52d7c895b7a7485465ca8d9/tensorflow/lite/kernels/while.cc) could be tricked into a scneario where both the body and the loop subgraphs are the same. Evaluating one of the subgraphs means calling the `Eval` function for the other and this quickly exhaust all stack space. ### Patches We have patched the issue in GitHub commit [9c1dc920d8ffb4893d6c9d27d1f039607b326743](https://github.com/tensorflow/tensorflow/commit/9c1dc920d8ffb4893d6c9d27d1f039607b326743) (for the `While` operator) and in GitHub commit [c6173f5fe66cdbab74f4f869311fe6aae2ba35f4](https://github.com/tensorflow/tensorflow/commit/c6173f5fe66cdbab74f4f869311fe6aae2ba35f4) (in general). The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. ### 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.

CVE-2021-29591 Affected Tensorflow Versions

12 component(s)
Fixed Versions:
2.1.42.2.32.3.32.4.2
Product / Package Ecosystem Affected Versions Fixed Version
tensorflow
pypi/tensorflow
PyPI
< 2.1.4
2.1.4
tensorflow
pypi/tensorflow
PyPI
≥ 2.2.0
< 2.2.3
2.2.3
tensorflow
pypi/tensorflow
PyPI
≥ 2.3.0
< 2.3.3
2.3.3
tensorflow
pypi/tensorflow
PyPI
≥ 2.4.0
< 2.4.2
2.4.2
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
< 2.1.4
2.1.4
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.2.0
< 2.2.3
2.2.3
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.3.0
< 2.3.3
2.3.3
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.4.0
< 2.4.2
2.4.2
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
< 2.1.4
2.1.4
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.2.0
< 2.2.3
2.2.3
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.3.0
< 2.3.3
2.3.3
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.4.0
< 2.4.2
2.4.2

References

GitHub Advisory / Wiki ADVISORY
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cwv3-863g-39vx
NVD — CVE-2021-29591 NVD
https://nvd.nist.gov/vuln/detail/CVE-2021-29591
Security Fix Commit FIX COMMIT
https://github.com/tensorflow/tensorflow/commit/9c1dc920d8ffb4893d6c9d27d1f039607b326743
Security Fix Commit FIX COMMIT
https://github.com/tensorflow/tensorflow/commit/c6173f5fe66cdbab74f4f869311fe6aae2ba35f4
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-519.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-717.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-228.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow/blob/106d8f4fb89335a2c52d7c895b7a7485465ca8d9/tensorflow/lite/kernels/while.cc

Frequently Asked Questions

What is CVE-2021-29591?
CVE-2021-29591 is a security vulnerability in Tensorflow involving Stack overflow due to looping TFLite subgraph under CWE-835: Loop with Unreachable Exit Condition ('Infinite Loop').
Which Tensorflow versions are affected?
Affected versions include releases prior to 2.1.4, 2.2.3, 2.3.3, 2.4.2 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.
What version fixes CVE-2021-29591?
Upgrading to 2.1.4, 2.2.3, 2.3.3, 2.4.2 (or the latest patched release for your respective branch) resolves the vulnerability.
Is tensorflow affected?
Yes, tensorflow is affected in releases prior to 2.1.4, 2.2.3, 2.3.3, 2.4.2. Upgrade your dependency to 2.1.4, 2.2.3, 2.3.3, 2.4.2 or later.
Is tensorflow-cpu affected?
Yes, tensorflow-cpu is affected in releases prior to 2.1.4, 2.2.3, 2.3.3, 2.4.2. Upgrade your dependency to 2.1.4, 2.2.3, 2.3.3, 2.4.2 or later.
What is the CVSS score of CVE-2021-29591?
CVE-2021-29591 has a CVSS v3.1 base score of 7.3 (HIGH) with vector string CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H.
What CWE is associated with CVE-2021-29591?
CVE-2021-29591 is classified under CWE-835: Loop with Unreachable Exit Condition ('Infinite Loop') (The product contains an iteration or loop with an exit condition that cannot be reached, i.e., an infinite loop.).
How can I check PyPI dependencies for CVE-2021-29591?
Run the dependency tree command: 'pip show tensorflow'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
View Raw JSON 
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  "aliases" : [ "CVE-2021-29591" ],
  "summary" : "Stack overflow due to looping TFLite subgraph",
  "details" : "### Impact\nTFlite graphs must not have loops between nodes. However, this condition was not checked and an attacker could craft models that would result in infinite loop during evaluation. In certain cases, the infinite loop would be replaced by stack overflow due to too many recursive calls.\n\nFor example, the [`While` implementation](https://github.com/tensorflow/tensorflow/blob/106d8f4fb89335a2c52d7c895b7a7485465ca8d9/tensorflow/lite/kernels/while.cc) could be tricked into a scneario where both the body and the loop subgraphs are the same. Evaluating one of the subgraphs means calling the `Eval` function for the other and this quickly exhaust all stack space.\n    \n### Patches \nWe have patched the issue in GitHub commit [9c1dc920d8ffb4893d6c9d27d1f039607b326743](https://github.com/tensorflow/tensorflow/commit/9c1dc920d8ffb4893d6c9d27d1f039607b326743) (for the `While` operator) and in GitHub commit [c6173f5fe66cdbab74f4f869311fe6aae2ba35f4](https://github.com/tensorflow/tensorflow/commit/c6173f5fe66cdbab74f4f869311fe6aae2ba35f4) (in general).\n    \nThe fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.\n\n### For more information\nPlease 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.\n\n### Attribution \nThis vulnerability has been reported by members of the Aivul Team from Qihoo 360.",
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}