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Security Advisories: GSA_kwCzR0hTQS1tZzY2LXF2YzUtcm05M84AArBK
Missing validation causes denial of service via `SparseTensorToCSRSparseMatrix`
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.
Permalink: https://github.com/advisories/GHSA-mg66-qvc5-rm93JSON: https://advisories.ecosyste.ms/api/v1/advisories/GSA_kwCzR0hTQS1tZzY2LXF2YzUtcm05M84AArBK
Source: GitHub Advisory Database
Origin: Unspecified
Severity: Moderate
Classification: General
Published: almost 2 years ago
Updated: about 1 year ago
CVSS Score: 5.5
CVSS vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Identifiers: GHSA-mg66-qvc5-rm93, CVE-2022-29198
References:
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mg66-qvc5-rm93
- https://nvd.nist.gov/vuln/detail/CVE-2022-29198
- https://github.com/tensorflow/tensorflow/commit/ea50a40e84f6bff15a0912728e35b657548cef11
- https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/sparse/sparse_tensor_to_csr_sparse_matrix_op.cc#L65-L119
- https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4
- https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2
- https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1
- https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0
- https://github.com/advisories/GHSA-mg66-qvc5-rm93
Blast Radius: 26.8
Affected Packages
pypi:tensorflow-gpu
Dependent packages: 146Dependent repositories: 11,499
Downloads: 350,104 last month
Affected Version Ranges: >= 2.8.0, < 2.8.1, >= 2.7.0, < 2.7.2, < 2.6.4
Fixed in: 2.8.1, 2.7.2, 2.6.4
All affected versions: 0.12.0, 0.12.1, 1.0.0, 1.0.1, 1.1.0, 1.2.0, 1.2.1, 1.3.0, 1.4.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.7.0, 1.7.1, 1.8.0, 1.9.0, 1.10.0, 1.10.1, 1.11.0, 1.12.0, 1.12.2, 1.12.3, 1.13.1, 1.13.2, 1.14.0, 1.15.0, 1.15.2, 1.15.3, 1.15.4, 1.15.5, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.0.4, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.7.0, 2.7.1, 2.8.0
All unaffected versions: 2.6.4, 2.6.5, 2.7.2, 2.7.3, 2.7.4, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.10.0, 2.10.1, 2.11.0, 2.12.0
pypi:tensorflow-cpu
Dependent packages: 71Dependent repositories: 2,483
Downloads: 940,986 last month
Affected Version Ranges: >= 2.8.0, < 2.8.1, >= 2.7.0, < 2.7.2, < 2.6.4
Fixed in: 2.8.1, 2.7.2, 2.6.4
All affected versions: 1.15.0, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.7.0, 2.7.1, 2.8.0
All unaffected versions: 2.6.4, 2.6.5, 2.7.2, 2.7.3, 2.7.4, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.10.0, 2.10.1, 2.11.0, 2.11.1, 2.12.0, 2.12.1, 2.13.0, 2.13.1, 2.14.0, 2.14.1, 2.15.0, 2.15.1, 2.16.1
pypi:tensorflow
Dependent packages: 1,733Dependent repositories: 73,755
Downloads: 22,369,513 last month
Affected Version Ranges: >= 2.8.0, < 2.8.1, >= 2.7.0, < 2.7.2, < 2.6.4
Fixed in: 2.8.1, 2.7.2, 2.6.4
All affected versions: 0.12.0, 0.12.1, 1.0.0, 1.0.1, 1.1.0, 1.2.0, 1.2.1, 1.3.0, 1.4.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.7.0, 1.7.1, 1.8.0, 1.9.0, 1.10.0, 1.10.1, 1.11.0, 1.12.0, 1.12.2, 1.12.3, 1.13.1, 1.13.2, 1.14.0, 1.15.0, 1.15.2, 1.15.3, 1.15.4, 1.15.5, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.0.4, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.7.0, 2.7.1, 2.8.0
All unaffected versions: 2.6.4, 2.6.5, 2.7.2, 2.7.3, 2.7.4, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.10.0, 2.10.1, 2.11.0, 2.11.1, 2.12.0, 2.12.1, 2.13.0, 2.13.1, 2.14.0, 2.14.1, 2.15.0, 2.15.1, 2.16.1