CVE-2021-29612
published 2021-05-14CVE-2021-29612: TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a heap buffer overflow in Eigen implementation of…
PriorityP337high7.8CVSS 3.1
AVLACLPRLUINSUCHIHAH
EPSS
0.29%
20.7th percentile
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a heap buffer overflow in Eigen implementation of `tf.raw_ops.BandedTriangularSolve`. The implementation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/linalg/banded_triangular_solve_op.cc#L269-L278) calls `ValidateInputTensors` for input validation but fails to validate that the two tensors are not empty. Furthermore, since `OP_REQUIRES` macro only stops execution of current function after setting `ctx->status()` to a non-OK value, callers of helper functions that use `OP_REQUIRES` must check value of `ctx->status()` before continuing. This doesn't happen in this op's implementation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/linalg/banded_triangular_solve_op.cc#L219), hence the validation that is present is also not effective. 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.
Affected
15 ranges
| Vendor | Product | Version range | Fixed in |
|---|---|---|---|
| debian | tensorflow | — | — |
| tensorflow | < 2.1.4 | 2.1.4 | |
| tensorflow | >= 2.2.0 < 2.2.3 | 2.2.3 | |
| tensorflow | >= 2.3.0 < 2.3.3 | 2.3.3 | |
| tensorflow | >= 2.4.0 < 2.4.2 | 2.4.2 | |
| intel | optimization_for_tensorflow | < 0ab290774f91a23bebe30a358fde4e53ab4876a0 | 0ab290774f91a23bebe30a358fde4e53ab4876a0 |
| intel | optimization_for_tensorflow | >= 0 < 2.1.4 | 2.1.4 |
| intel | optimization_for_tensorflow | >= 0 < ba6822bd7b7324ba201a28b2f278c29a98edbef2 | ba6822bd7b7324ba201a28b2f278c29a98edbef2 |
| intel | optimization_for_tensorflow | >= 2.2.0 < 2.2.3 | 2.2.3 |
| intel | optimization_for_tensorflow | >= 2.3.0 < 2.3.3 | 2.3.3 |
| intel | optimization_for_tensorflow | >= 2.4.0 < 2.4.2 | 2.4.2 |
| tensorflow | tensorflow | < 2.1.4 | 2.1.4 |
| tensorflow | tensorflow | — | — |
| tensorflow | tensorflow | — | — |
| tensorflow | tensorflow | — | — |
CVSS provenance
nvdv3.17.8HIGHCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
nvdv2.04.6MEDIUMAV:L/AC:L/Au:N/C:P/I:P/A:P
vendor_debian3.6LOW
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Debian
CVE-2021-29612: tensorflow - TensorFlow is an end-to-end open source platform for machine learning. An attack...
vendor_debian·2021·CVSS 3.6
CVE-2021-29612 [LOW] CVE-2021-29612: tensorflow - TensorFlow is an end-to-end open source platform for machine learning. An attack...
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a heap buffer overflow in Eigen implementation of `tf.raw_ops.BandedTriangularSolve`. The implementation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/linalg/banded_triangular_solve_op.cc#L269-L278) calls `ValidateInputTensors` for input validation but fails to validate that the two tensors are not empty. Furthermore, since `OP_REQUIRES` macro only stops execution of current function after setting `ctx->status()` to a non-OK value, callers of helper functions that use `OP_REQUIRES` must check value of `ctx->status()` before continuing. This doesn't happen in this op's implementation(https://github.com/tensorflow/tensorflow/blob/eccb
OSV
Heap buffer overflow in `BandedTriangularSolve`
osv·2021-05-21
CVE-2021-29612 [LOW] Heap buffer overflow in `BandedTriangularSolve`
Heap buffer overflow in `BandedTriangularSolve`
### Impact
An attacker can trigger a heap buffer overflow in Eigen implementation of `tf.raw_ops.BandedTriangularSolve`:
```python
import tensorflow as tf
import numpy as np
matrix_array = np.array([])
matrix_tensor = tf.convert_to_tensor(np.reshape(matrix_array,(0,1)),dtype=tf.float32)
rhs_array = np.array([1,1])
rhs_tensor = tf.convert_to_tensor(np.reshape(rhs_array,(1,2)),dtype=tf.float32)
tf.raw_ops.BandedTriangularSolve(matrix=matrix_tensor,rhs=rhs_tensor)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/linalg/banded_triangular_solve_op.cc#L269-L278) calls `ValidateInputTensors` for input validation but fails to validate that the two tensors are n
GHSA
Heap buffer overflow in `BandedTriangularSolve`
ghsa·2021-05-21
CVE-2021-29612 [LOW] CWE-120 Heap buffer overflow in `BandedTriangularSolve`
Heap buffer overflow in `BandedTriangularSolve`
### Impact
An attacker can trigger a heap buffer overflow in Eigen implementation of `tf.raw_ops.BandedTriangularSolve`:
```python
import tensorflow as tf
import numpy as np
matrix_array = np.array([])
matrix_tensor = tf.convert_to_tensor(np.reshape(matrix_array,(0,1)),dtype=tf.float32)
rhs_array = np.array([1,1])
rhs_tensor = tf.convert_to_tensor(np.reshape(rhs_array,(1,2)),dtype=tf.float32)
tf.raw_ops.BandedTriangularSolve(matrix=matrix_tensor,rhs=rhs_tensor)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/linalg/banded_triangular_solve_op.cc#L269-L278) calls `ValidateInputTensors` for input validation but fails to validate that the two tensors are n
OSV
CVE-2021-29612: TensorFlow is an end-to-end open source platform for machine learning
osv·2021-05-14
CVE-2021-29612 CVE-2021-29612: TensorFlow is an end-to-end open source platform for machine learning
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a heap buffer overflow in Eigen implementation of `tf.raw_ops.BandedTriangularSolve`. The implementation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/linalg/banded_triangular_solve_op.cc#L269-L278) calls `ValidateInputTensors` for input validation but fails to validate that the two tensors are not empty. Furthermore, since `OP_REQUIRES` macro only stops execution of current function after setting `ctx->status()` to a non-OK value, callers of helper functions that use `OP_REQUIRES` must check value of `ctx->status()` before continuing. This doesn't happen in this op's implementation(https://github.com/tensorflow/tensorflow/blob/eccb
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
https://github.com/tensorflow/tensorflow/commit/0ab290774f91a23bebe30a358fde4e53ab4876a0https://github.com/tensorflow/tensorflow/commit/ba6822bd7b7324ba201a28b2f278c29a98edbef2https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2xgj-xhgf-ggjvhttps://github.com/tensorflow/tensorflow/commit/0ab290774f91a23bebe30a358fde4e53ab4876a0https://github.com/tensorflow/tensorflow/commit/ba6822bd7b7324ba201a28b2f278c29a98edbef2https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2xgj-xhgf-ggjv
2021-05-14
Published