CVE-2021-37647: Tensorflow Null Pointer Dereference Vulnerability
HIGHCVE-2021-37647 is a HIGH (CVSS 7.7) null pointer dereference vulnerability (CWE-476: NULL Pointer Dereference) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves null pointer dereference in `sparsetensorslicedataset`. Remediation is available by upgrading affected packages to version 2.3.4, 2.4.3, 2.5.1.
CVE-2021-37647 at a Glance
Security Impact
CVSS: 7.7
The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:H).
How to Fix CVE-2021-37647
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.
pip install tensorflow>=2.3.4
pip install tensorflow>=2.4.3
pip install tensorflow>=2.5.1
pip install tensorflow-cpu>=2.3.4
pip install tensorflow-cpu>=2.4.3
pip install tensorflow-cpu>=2.5.1
pip install tensorflow-gpu>=2.3.4
pip install tensorflow-gpu>=2.4.3
pip install tensorflow-gpu>=2.5.1
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-2021-37647, 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 2.3.4), 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-476: NULL Pointer Dereference, where the product dereferences a pointer that it expects to be valid but is null. 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
CVE-2021-37647 Affected Tensorflow Versions
9 component(s)| Product / Package | Ecosystem | Affected Versions | Fixed Version |
|---|---|---|---|
|
tensorflow
|
PyPI |
< 2.3.4
|
2.3.4
|
|
tensorflow
|
PyPI |
≥ 2.4.0
< 2.4.3
|
2.4.3
|
|
tensorflow
|
PyPI |
≥ 2.5.0
< 2.5.1
All 1 versions
2.5.0
|
2.5.1
|
|
tensorflow-cpu
|
PyPI |
< 2.3.4
|
2.3.4
|
|
tensorflow-cpu
|
PyPI |
≥ 2.4.0
< 2.4.3
|
2.4.3
|
|
tensorflow-cpu
|
PyPI |
≥ 2.5.0
< 2.5.1
All 1 versions
2.5.0
|
2.5.1
|
|
tensorflow-gpu
|
PyPI |
< 2.3.4
|
2.3.4
|
|
tensorflow-gpu
|
PyPI |
≥ 2.4.0
< 2.4.3
|
2.4.3
|
|
tensorflow-gpu
|
PyPI |
≥ 2.5.0
< 2.5.1
All 1 versions
2.5.0
|
2.5.1
|
References
Frequently Asked Questions
What is CVE-2021-37647?
Which Tensorflow versions are affected?
What version fixes CVE-2021-37647?
Is tensorflow affected?
Is tensorflow-cpu affected?
What is the CVSS score of CVE-2021-37647?
What CWE is associated with CVE-2021-37647?
How can I check PyPI dependencies for CVE-2021-37647?
Machine-readable OSV JSON
OSV v1.5 Schema
{
"schema_version" : "1.4.0",
"id" : "GHSA-c5x2-p679-95wc",
"modified" : "2024-11-13T17:20:44Z",
"published" : "2021-08-25T14:43:32Z",
"aliases" : [ "CVE-2021-37647" ],
"summary" : "Null pointer dereference in `SparseTensorSliceDataset`",
"details" : "### Impact\nWhen a user does not supply arguments that determine a valid sparse tensor, `tf.raw_ops.SparseTensorSliceDataset` implementation can be made to dereference a null pointer:\n\n```python\nimport tensorflow as tf\n\ntf.raw_ops.SparseTensorSliceDataset(\n indices=[[],[],[]],\n values=[1,2,3],\n dense_shape=[3,3])\n```\n \nThe [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L240-L251) has some argument validation but fails to consider the case when either `indices` or `values` are provided for an empty sparse tensor when the other is not.\n\nIf `indices` is empty (as in the example above), then [code that performs validation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L260-L261) (i.e., checking that the indices are monotonically increasing) results in a null pointer dereference: \n\n```cc\n for (int64_t i = 0; i < indices->dim_size(0); ++i) {\n int64_t next_batch_index = indices->matrix<int64>()(i, 0);\n ...\n }\n```\n\nIf `indices` as provided by the user is empty, then `indices` in the C++ code above is backed by an empty `std::vector`, hence calling `indices->dim_size(0)` results in null pointer dereferencing (same as calling `std::vector::at()` on an empty vector).\n\n### Patches\nWe have patched the issue in GitHub commit [02cc160e29d20631de3859c6653184e3f876b9d7](https://github.com/tensorflow/tensorflow/commit/02cc160e29d20631de3859c6653184e3f876b9d7).\n\nThe fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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.",
"severity" : [ {
"type" : "CVSS_V3",
"score" : "CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:H"
}, {
"type" : "CVSS_V4",
"score" : "CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:N/VC:N/VI:H/VA:H/SC:N/SI:N/SA:N"
} ],
"affected" : [ {
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},
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"events" : [ {
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}, {
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}, {
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}, {
"fixed" : "2.5.1"
} ]
} ],
"versions" : [ "2.5.0" ]
} ],
"references" : [ {
"type" : "WEB",
"url" : "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c5x2-p679-95wc"
}, {
"type" : "ADVISORY",
"url" : "https://nvd.nist.gov/vuln/detail/CVE-2021-37647"
}, {
"type" : "WEB",
"url" : "https://github.com/tensorflow/tensorflow/commit/02cc160e29d20631de3859c6653184e3f876b9d7"
}, {
"type" : "WEB",
"url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-560.yaml"
}, {
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"url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-758.yaml"
}, {
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"url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-269.yaml"
}, {
"type" : "PACKAGE",
"url" : "https://github.com/tensorflow/tensorflow"
} ],
"database_specific" : {
"cwe_ids" : [ "CWE-476" ],
"severity" : "HIGH",
"github_reviewed" : true,
"github_reviewed_at" : "2021-08-23T19:27:50Z",
"nvd_published_at" : "2021-08-12T19:15:00Z"
}
}