CVE-2021-41219: Tensorflow Undefined Behavior Vulnerability
HIGHCVE-2021-41219 is a HIGH (CVSS 7.8) undefined behavior vulnerability (CWE-125: Out-of-bounds Read) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves undefined behavior via `nullptr` reference binding in sparse matrix multiplication. Remediation is available by upgrading affected packages to version 2.6.1, 2.5.2, 2.4.4.
CVE-2021-41219 at a Glance
Security Impact
CVSS: 7.8
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:H/A:H).
How to Fix CVE-2021-41219
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>=2.6.1
pip install tensorflow>=2.5.2
pip install tensorflow>=2.4.4
pip install tensorflow-cpu>=2.6.1
pip install tensorflow-cpu>=2.5.2
pip install tensorflow-cpu>=2.4.4
pip install tensorflow-gpu>=2.6.1
pip install tensorflow-gpu>=2.5.2
pip install tensorflow-gpu>=2.4.4
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-2021-41219, 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 2.6.1), 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-125: Out-of-bounds Read, where the product reads data past the end, or before the beginning, of the intended buffer. 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-2021-41219 Affected Tensorflow Versions
9 component(s)| Product / Package | Ecosystem | Affected Versions | Fixed Version |
|---|---|---|---|
|
tensorflow
|
PyPI |
≥ 2.6.0
< 2.6.1
|
2.6.1
|
|
tensorflow
|
PyPI |
≥ 2.5.0
< 2.5.2
|
2.5.2
|
|
tensorflow
|
PyPI |
< 2.4.4
|
2.4.4
|
|
tensorflow-cpu
|
PyPI |
≥ 2.6.0
< 2.6.1
|
2.6.1
|
|
tensorflow-cpu
|
PyPI |
≥ 2.5.0
< 2.5.2
|
2.5.2
|
|
tensorflow-cpu
|
PyPI |
< 2.4.4
|
2.4.4
|
|
tensorflow-gpu
|
PyPI |
≥ 2.6.0
< 2.6.1
|
2.6.1
|
|
tensorflow-gpu
|
PyPI |
≥ 2.5.0
< 2.5.2
|
2.5.2
|
|
tensorflow-gpu
|
PyPI |
< 2.4.4
|
2.4.4
|
References
Frequently Asked Questions
What is CVE-2021-41219?
Which Tensorflow versions are affected?
What version fixes CVE-2021-41219?
Is tensorflow affected?
Is tensorflow-cpu affected?
What is the CVSS score of CVE-2021-41219?
What CWE is associated with CVE-2021-41219?
How can I check PyPI dependencies for CVE-2021-41219?
Machine-readable OSV JSON
OSV v1.5 Schema
{
"schema_version" : "1.4.0",
"id" : "GHSA-4f99-p9c2-3j8x",
"modified" : "2024-11-07T22:14:20Z",
"published" : "2021-11-10T18:51:51Z",
"aliases" : [ "CVE-2021-41219" ],
"summary" : "Undefined behavior via `nullptr` reference binding in sparse matrix multiplication",
"details" : "### Impact\nThe [code for sparse matrix multiplication](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/sparse_matmul_op.cc#L954-L1086) is vulnerable to undefined behavior via binding a reference to `nullptr`:\n\n```python\nimport tensorflow as tf\n \ntf.raw_ops.SparseMatMul(\n a=[[1.0,1.0,1.0]],\n b=[[],[],[]],\n transpose_a=False,\n transpose_b=False,\n a_is_sparse=False, \n b_is_sparse=True)\n```\n\nThis occurs whenever the dimensions of `a` or `b` are 0 or less. In the case on one of these is 0, an empty output tensor should be allocated (to conserve the invariant that output tensors are always allocated when the operation is successful) but nothing should be written to it (that is, we should return early from the kernel implementation). Otherwise, attempts to write to this empty tensor would result in heap OOB access.\n\n### Patches\nWe have patched the issue in GitHub commit [e6cf28c72ba2eb949ca950d834dd6d66bb01cfae](https://github.com/tensorflow/tensorflow/commit/e6cf28c72ba2eb949ca950d834dd6d66bb01cfae).\n\nThe fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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.\n",
"severity" : [ {
"type" : "CVSS_V3",
"score" : "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H"
} ],
"affected" : [ {
"package" : {
"ecosystem" : "PyPI",
"name" : "tensorflow"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "2.6.0"
}, {
"fixed" : "2.6.1"
} ]
} ]
}, {
"package" : {
"ecosystem" : "PyPI",
"name" : "tensorflow"
},
"ranges" : [ {
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"introduced" : "2.5.0"
}, {
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} ]
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}, {
"package" : {
"ecosystem" : "PyPI",
"name" : "tensorflow"
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}, {
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"name" : "tensorflow-cpu"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "2.6.0"
}, {
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} ]
} ]
}, {
"package" : {
"ecosystem" : "PyPI",
"name" : "tensorflow-cpu"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "2.5.0"
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} ]
} ]
}, {
"package" : {
"ecosystem" : "PyPI",
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},
"ranges" : [ {
"type" : "ECOSYSTEM",
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}, {
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} ]
} ]
}, {
"package" : {
"ecosystem" : "PyPI",
"name" : "tensorflow-gpu"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "2.6.0"
}, {
"fixed" : "2.6.1"
} ]
} ]
}, {
"package" : {
"ecosystem" : "PyPI",
"name" : "tensorflow-gpu"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "2.5.0"
}, {
"fixed" : "2.5.2"
} ]
} ]
}, {
"package" : {
"ecosystem" : "PyPI",
"name" : "tensorflow-gpu"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "0"
}, {
"fixed" : "2.4.4"
} ]
} ]
} ],
"references" : [ {
"type" : "WEB",
"url" : "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4f99-p9c2-3j8x"
}, {
"type" : "ADVISORY",
"url" : "https://nvd.nist.gov/vuln/detail/CVE-2021-41219"
}, {
"type" : "WEB",
"url" : "https://github.com/tensorflow/tensorflow/commit/e6cf28c72ba2eb949ca950d834dd6d66bb01cfae"
}, {
"type" : "WEB",
"url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-628.yaml"
}, {
"type" : "WEB",
"url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-826.yaml"
}, {
"type" : "WEB",
"url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-411.yaml"
}, {
"type" : "PACKAGE",
"url" : "https://github.com/tensorflow/tensorflow"
} ],
"database_specific" : {
"cwe_ids" : [ "CWE-125", "CWE-824" ],
"severity" : "HIGH",
"github_reviewed" : true,
"github_reviewed_at" : "2021-11-08T22:08:27Z",
"nvd_published_at" : "2021-11-05T21:15:00Z"
}
}