CVE-2021-29532: Tensorflow Heap Out Of Bounds Read Vulnerability

LOW
Advisory Identifier: GHSA-j47f-4232-hvv8
CVSS 2.5
CWE-125
Published
Advisory Summary

CVE-2021-29532 is a LOW (CVSS 2.5) heap out of bounds read vulnerability (CWE-125: Out-of-bounds Read) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves heap out of bounds read in `raggedcross`. Remediation is available by upgrading affected packages to version 2.1.4, 2.2.3, 2.3.3, 2.4.2.

CVE-2021-29532 at a Glance

CVE Identifier CVE-2021-29532
GHSA Identifier GHSA-j47f-4232-hvv8
Severity LOW
CVSS v3.1 Base Score 2.5
CWE Classification CWE-125: Out-of-bounds Read
Affected Product Tensorflow
Package Ecosystem PyPI
Published Date
Last Updated

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).

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

How to Fix CVE-2021-29532

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-2021-29532, 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-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

### Impact An attacker can force accesses outside the bounds of heap allocated arrays by passing in invalid tensor values to `tf.raw_ops.RaggedCross`: ```python import tensorflow as tf ragged_values = [] ragged_row_splits = [] sparse_indices = [] sparse_values = [] sparse_shape = [] dense_inputs_elem = tf.constant([], shape=[92, 0], dtype=tf.int64) dense_inputs = [dense_inputs_elem] input_order = "R" hashed_output = False num_buckets = 0 hash_key = 0 tf.raw_ops.RaggedCross(ragged_values=ragged_values, ragged_row_splits=ragged_row_splits, sparse_indices=sparse_indices, sparse_values=sparse_values, sparse_shape=sparse_shape, dense_inputs=dense_inputs, input_order=input_order, hashed_output=hashed_output, num_buckets=num_buckets, hash_key=hash_key, out_values_type=tf.int64, out_row_splits_type=tf.int64) ``` This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/efea03b38fb8d3b81762237dc85e579cc5fc6e87/tensorflow/core/kernels/ragged_cross_op.cc#L456-L487) lacks validation for the user supplied arguments: ```cc int next_ragged = 0; int next_sparse = 0; int next_dense = 0; for (char c : input_order_) { if (c == 'R') { TF_RETURN_IF_ERROR(BuildRaggedFeatureReader( ragged_values_list[next_ragged], ragged_splits_list[next_ragged], features)); next_ragged++; } else if (c == 'S') { TF_RETURN_IF_ERROR(BuildSparseFeatureReader( sparse_indices_list[next_sparse], sparse_values_list[next_sparse], batch_size, features)); next_sparse++; } else if (c == 'D') { TF_RETURN_IF_ERROR( BuildDenseFeatureReader(dense_list[next_dense++], features)); } ... } ``` Each of the above branches call a helper function after accessing array elements via a `*_list[next_*]` pattern, followed by incrementing the `next_*` index. However, as there is no validation that the `next_*` values are in the valid range for the corresponding `*_list` arrays, this results in heap OOB reads. ### Patches We have patched the issue in GitHub commit [44b7f486c0143f68b56c34e2d01e146ee445134a](https://github.com/tensorflow/tensorflow/commit/44b7f486c0143f68b56c34e2d01e146ee445134a). 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 Ying Wang and Yakun Zhang of Baidu X-Team.

CVE-2021-29532 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
< 2.1.4
2.1.4
tensorflow
PyPI
≥ 2.2.0
< 2.2.3
2.2.3
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
< 2.1.4
2.1.4
tensorflow-cpu
PyPI
≥ 2.2.0
< 2.2.3
2.2.3
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
< 2.1.4
2.1.4
tensorflow-gpu
PyPI
≥ 2.2.0
< 2.2.3
2.2.3
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-2021-29532?
CVE-2021-29532 is a security vulnerability in Tensorflow involving Heap out of bounds read in `RaggedCross` under CWE-125: Out-of-bounds Read.
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-2021-29532?
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-2021-29532?
CVE-2021-29532 has a CVSS v3.1 base score of 2.5 (LOW) with vector string CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L.
What CWE is associated with CVE-2021-29532?
CVE-2021-29532 is classified under CWE-125: Out-of-bounds Read (The product reads data past the end, or before the beginning, of the intended buffer.).
How can I check PyPI dependencies for CVE-2021-29532?
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
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-j47f-4232-hvv8",
  "modified" : "2024-10-30T23:21:38Z",
  "published" : "2021-05-21T14:22:17Z",
  "aliases" : [ "CVE-2021-29532" ],
  "summary" : "Heap out of bounds read in `RaggedCross`",
  "details" : "### Impact\nAn attacker can force accesses outside the bounds of heap allocated arrays by passing in invalid tensor values to `tf.raw_ops.RaggedCross`:\n\n```python\nimport tensorflow as tf\n\nragged_values = []\nragged_row_splits = [] \nsparse_indices = []\nsparse_values = []\nsparse_shape = []\n\ndense_inputs_elem = tf.constant([], shape=[92, 0], dtype=tf.int64)\ndense_inputs = [dense_inputs_elem]\n\ninput_order = \"R\"\nhashed_output = False\nnum_buckets = 0\nhash_key = 0 \n\ntf.raw_ops.RaggedCross(ragged_values=ragged_values,\n    ragged_row_splits=ragged_row_splits,\n    sparse_indices=sparse_indices,\n    sparse_values=sparse_values,\n    sparse_shape=sparse_shape,\n    dense_inputs=dense_inputs,\n    input_order=input_order,\n    hashed_output=hashed_output,\n    num_buckets=num_buckets,\n    hash_key=hash_key,\n    out_values_type=tf.int64,\n    out_row_splits_type=tf.int64)\n```\n\nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/efea03b38fb8d3b81762237dc85e579cc5fc6e87/tensorflow/core/kernels/ragged_cross_op.cc#L456-L487) lacks validation for the user supplied arguments:\n\n```cc\nint next_ragged = 0;\nint next_sparse = 0;\nint next_dense = 0;\nfor (char c : input_order_) {\n  if (c == 'R') {\n    TF_RETURN_IF_ERROR(BuildRaggedFeatureReader(\n        ragged_values_list[next_ragged], ragged_splits_list[next_ragged],\n        features));\n    next_ragged++;\n  } else if (c == 'S') {\n    TF_RETURN_IF_ERROR(BuildSparseFeatureReader(\n        sparse_indices_list[next_sparse], sparse_values_list[next_sparse],\n        batch_size, features));\n    next_sparse++;\n  } else if (c == 'D') {\n    TF_RETURN_IF_ERROR(\n        BuildDenseFeatureReader(dense_list[next_dense++], features));\n  }\n  ...\n}\n```\n\nEach of the above branches call a helper function after accessing array elements via a `*_list[next_*]` pattern, followed by incrementing the `next_*` index. However, as there is no validation that the `next_*` values are in the valid range for the corresponding `*_list` arrays, this results in heap OOB reads.\n\n### Patches\nWe have patched the issue in GitHub commit [44b7f486c0143f68b56c34e2d01e146ee445134a](https://github.com/tensorflow/tensorflow/commit/44b7f486c0143f68b56c34e2d01e146ee445134a).\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 Ying Wang and Yakun Zhang 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",
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  } ],
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  }, {
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    } ]
  } ],
  "references" : [ {
    "type" : "WEB",
    "url" : "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j47f-4232-hvv8"
  }, {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2021-29532"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/tensorflow/tensorflow/commit/44b7f486c0143f68b56c34e2d01e146ee445134a"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-460.yaml"
  }, {
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  }, {
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    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-169.yaml"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/tensorflow/tensorflow"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-125" ],
    "severity" : "LOW",
    "github_reviewed" : true,
    "github_reviewed_at" : "2021-05-18T22:54:15Z",
    "nvd_published_at" : "2021-05-14T20:15:00Z"
  }
}