CVE-2021-29521: Tensorflow Segfault Vulnerability
LOWCVE-2021-29521 is a LOW (CVSS 2.5) segfault vulnerability (CWE-131: Incorrect Calculation of Buffer Size) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves segfault in sparsecountsparseoutput. Remediation is available by upgrading affected packages to version 2.3.3, 2.4.2.
CVE-2021-29521 at a Glance
Security Impact
CVSS: 2.5
The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L).
How to Fix CVE-2021-29521
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>=2.3.3
pip install tensorflow>=2.4.2
pip install tensorflow-cpu>=2.3.3
pip install tensorflow-cpu>=2.4.2
pip install tensorflow-gpu>=2.3.3
pip install tensorflow-gpu>=2.4.2
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-2021-29521, 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 2.3.3), 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-131: Incorrect Calculation of Buffer Size, where the product does not correctly calculate the size to be used when allocating a buffer, which could lead to a buffer overflow. 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-2021-29521 Affected Tensorflow Versions
6 component(s)| Product / Package | Ecosystem | Affected Versions | Fixed Version |
|---|---|---|---|
|
tensorflow
|
PyPI |
≥ 2.3.0
< 2.3.3
|
2.3.3
|
|
tensorflow
|
PyPI |
≥ 2.4.0
< 2.4.2
|
2.4.2
|
|
tensorflow-cpu
|
PyPI |
≥ 2.3.0
< 2.3.3
|
2.3.3
|
|
tensorflow-cpu
|
PyPI |
≥ 2.4.0
< 2.4.2
|
2.4.2
|
|
tensorflow-gpu
|
PyPI |
≥ 2.3.0
< 2.3.3
|
2.3.3
|
|
tensorflow-gpu
|
PyPI |
≥ 2.4.0
< 2.4.2
|
2.4.2
|
References
Frequently Asked Questions
What is CVE-2021-29521?
Which Tensorflow versions are affected?
What version fixes CVE-2021-29521?
Is tensorflow affected?
Is tensorflow-cpu affected?
What is the CVSS score of CVE-2021-29521?
What CWE is associated with CVE-2021-29521?
How can I check PyPI dependencies for CVE-2021-29521?
Machine-readable OSV JSON
OSV v1.5 Schema
{
"schema_version" : "1.4.0",
"id" : "GHSA-hr84-fqvp-48mm",
"modified" : "2024-10-28T21:21:03Z",
"published" : "2021-05-21T14:21:16Z",
"aliases" : [ "CVE-2021-29521" ],
"summary" : "Segfault in SparseCountSparseOutput",
"details" : "### Impact\nSpecifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken.\n\n```python\nimport tensorflow as tf\n\nindices = tf.constant([], shape=[0, 0], dtype=tf.int64)\nvalues = tf.constant([], shape=[0, 0], dtype=tf.int64)\ndense_shape = tf.constant([-100, -100, -100], shape=[3], dtype=tf.int64)\nweights = tf.constant([], shape=[0, 0], dtype=tf.int64)\n\ntf.raw_ops.SparseCountSparseOutput(indices=indices, values=values, dense_shape=dense_shape, weights=weights, minlength=79, maxlength=96, binary_output=False)\n```\n\nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap<T>` (i.e., [`std::vector<absl::flat_hash_map<int64,T>>`](https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure.\n\n```cc\n bool is_1d = shape.NumElements() == 1;\n int num_batches = is_1d ? 1 : shape.flat<int64>()(0);\n ...\n auto per_batch_counts = BatchedMap<W>(num_batches); \n```\n\nIf the `shape` tensor has more than one element, `num_batches` is the first value in `shape`.\n \nEnsuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue.\n\n### Patches\nWe have patched the issue in GitHub commit [c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5](https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5).\n\nThe fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3.\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 Yakun Zhang and Ying Wang of Baidu X-Team.",
"severity" : [ {
"type" : "CVSS_V3",
"score" : "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L"
}, {
"type" : "CVSS_V4",
"score" : "CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N"
} ],
"affected" : [ {
"package" : {
"ecosystem" : "PyPI",
"name" : "tensorflow"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "2.3.0"
}, {
"fixed" : "2.3.3"
} ]
} ]
}, {
"package" : {
"ecosystem" : "PyPI",
"name" : "tensorflow"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "2.4.0"
}, {
"fixed" : "2.4.2"
} ]
} ]
}, {
"package" : {
"ecosystem" : "PyPI",
"name" : "tensorflow-cpu"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "2.3.0"
}, {
"fixed" : "2.3.3"
} ]
} ]
}, {
"package" : {
"ecosystem" : "PyPI",
"name" : "tensorflow-cpu"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "2.4.0"
}, {
"fixed" : "2.4.2"
} ]
} ]
}, {
"package" : {
"ecosystem" : "PyPI",
"name" : "tensorflow-gpu"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "2.3.0"
}, {
"fixed" : "2.3.3"
} ]
} ]
}, {
"package" : {
"ecosystem" : "PyPI",
"name" : "tensorflow-gpu"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "2.4.0"
}, {
"fixed" : "2.4.2"
} ]
} ]
} ],
"references" : [ {
"type" : "WEB",
"url" : "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hr84-fqvp-48mm"
}, {
"type" : "ADVISORY",
"url" : "https://nvd.nist.gov/vuln/detail/CVE-2021-29521"
}, {
"type" : "WEB",
"url" : "https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5"
}, {
"type" : "WEB",
"url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-449.yaml"
}, {
"type" : "WEB",
"url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-647.yaml"
}, {
"type" : "WEB",
"url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-158.yaml"
} ],
"database_specific" : {
"cwe_ids" : [ "CWE-131" ],
"severity" : "LOW",
"github_reviewed" : true,
"github_reviewed_at" : "2021-05-18T23:23:47Z",
"nvd_published_at" : "2021-05-14T20:15:00Z"
}
}