GHSA-MG66-QVC5-RM93
Vulnerability from github – Published: 2022-05-24 22:08 – Updated: 2022-05-24 22:08
VLAI?
Summary
Missing validation causes denial of service via `SparseTensorToCSRSparseMatrix`
Details
Impact
The implementation of tf.raw_ops.SparseTensorToCSRSparseMatrix does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:
import tensorflow as tf
indices = tf.constant(53, shape=[3], dtype=tf.int64)
values = tf.constant(0.554979503, shape=[218650], dtype=tf.float32)
dense_shape = tf.constant(53, shape=[3], dtype=tf.int64)
tf.raw_ops.SparseTensorToCSRSparseMatrix(
indices=indices,
values=values,
dense_shape=dense_shape)
The code assumes dense_shape is a vector and indices is a matrix (as part of requirements for sparse tensors) but there is no validation for this:
const Tensor& indices = ctx->input(0);
const Tensor& values = ctx->input(1);
const Tensor& dense_shape = ctx->input(2);
const int rank = dense_shape.NumElements();
OP_REQUIRES(ctx, rank == 2 || rank == 3,
errors::InvalidArgument("SparseTensor must have rank 2 or 3; ",
"but indices has rank: ", rank));
auto dense_shape_vec = dense_shape.vec<int64_t>();
// ...
OP_REQUIRES_OK(
ctx,
coo_to_csr(batch_size, num_rows, indices.template matrix<int64_t>(),
batch_ptr.vec<int32>(), csr_row_ptr.vec<int32>(),
csr_col_ind.vec<int32>()));
Patches
We have patched the issue in GitHub commit ea50a40e84f6bff15a0912728e35b657548cef11.
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported by Neophytos Christou from Secure Systems Lab at Brown University.
Severity ?
5.5 (Medium)
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.6.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.7.0"
},
{
"fixed": "2.7.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.8.0"
},
{
"fixed": "2.8.1"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.6.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.7.0"
},
{
"fixed": "2.7.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.8.0"
},
{
"fixed": "2.8.1"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.6.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.7.0"
},
{
"fixed": "2.7.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.8.0"
},
{
"fixed": "2.8.1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2022-29198"
],
"database_specific": {
"cwe_ids": [
"CWE-20"
],
"github_reviewed": true,
"github_reviewed_at": "2022-05-24T22:08:45Z",
"nvd_published_at": "2022-05-20T22:16:00Z",
"severity": "MODERATE"
},
"details": "### Impact\nThe implementation of [`tf.raw_ops.SparseTensorToCSRSparseMatrix`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/sparse/sparse_tensor_to_csr_sparse_matrix_op.cc#L65-L119) does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack:\n\n```python\nimport tensorflow as tf\n\nindices = tf.constant(53, shape=[3], dtype=tf.int64)\nvalues = tf.constant(0.554979503, shape=[218650], dtype=tf.float32)\ndense_shape = tf.constant(53, shape=[3], dtype=tf.int64)\n \ntf.raw_ops.SparseTensorToCSRSparseMatrix(\n indices=indices,\n values=values,\n dense_shape=dense_shape)\n```\n\nThe code assumes `dense_shape` is a vector and `indices` is a matrix (as part of requirements for sparse tensors) but there is no validation for this:\n \n```cc\n const Tensor\u0026 indices = ctx-\u003einput(0);\n const Tensor\u0026 values = ctx-\u003einput(1);\n const Tensor\u0026 dense_shape = ctx-\u003einput(2);\n const int rank = dense_shape.NumElements();\n OP_REQUIRES(ctx, rank == 2 || rank == 3,\n errors::InvalidArgument(\"SparseTensor must have rank 2 or 3; \",\n \"but indices has rank: \", rank));\n auto dense_shape_vec = dense_shape.vec\u003cint64_t\u003e();\n // ...\n OP_REQUIRES_OK(\n ctx,\n coo_to_csr(batch_size, num_rows, indices.template matrix\u003cint64_t\u003e(),\n batch_ptr.vec\u003cint32\u003e(), csr_row_ptr.vec\u003cint32\u003e(),\n csr_col_ind.vec\u003cint32\u003e()));\n```\n\n### Patches\nWe have patched the issue in GitHub commit [ea50a40e84f6bff15a0912728e35b657548cef11](https://github.com/tensorflow/tensorflow/commit/ea50a40e84f6bff15a0912728e35b657548cef11).\n\nThe fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.",
"id": "GHSA-mg66-qvc5-rm93",
"modified": "2022-05-24T22:08:45Z",
"published": "2022-05-24T22:08:45Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mg66-qvc5-rm93"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-29198"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/ea50a40e84f6bff15a0912728e35b657548cef11"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/sparse/sparse_tensor_to_csr_sparse_matrix_op.cc#L65-L119"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "Missing validation causes denial of service via `SparseTensorToCSRSparseMatrix`"
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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