Vulnerability · Published May 14, 2021 · Assigned by GitHub_M
CVE-2021-29612Heap buffer overflow in `BandedTriangularSolve`
Low 3.6
In plain English
A low-severity buffer overflow in tensorflow from tensorflow. There are no confirmed reports of exploitation so far. The chance it is exploited in the next 30 days is estimated at 0.3% (higher than 21% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.
Official description
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 packages & fixed versions
| Ecosystem | Package | Fixed in | Advisory |
|---|---|---|---|
| PyPI | tensorflow | 2.3.3 | GHSA-2xgj-xhgf-ggjv |
| PyPI | tensorflow | 2.4.2 | GHSA-2xgj-xhgf-ggjv |
| PyPI | tensorflow | 2.1.4 | GHSA-2xgj-xhgf-ggjv |
| PyPI | tensorflow | 2.1.4, 2.2.3, 2.3.3, 2.4.2 | PYSEC-2021-249 |
| PyPI | tensorflow | 2.2.3 | GHSA-2xgj-xhgf-ggjv |
| PyPI | tensorflow-cpu | 2.4.2 | GHSA-2xgj-xhgf-ggjv |
| PyPI | tensorflow-cpu | 2.1.4 | GHSA-2xgj-xhgf-ggjv |
| PyPI | tensorflow-cpu | 2.2.3 | GHSA-2xgj-xhgf-ggjv |
| PyPI | tensorflow-cpu | 2.3.3 | GHSA-2xgj-xhgf-ggjv |
| PyPI | tensorflow-cpu | 2.1.4, 2.2.3, 2.3.3, 2.4.2 | PYSEC-2021-540 |
| PyPI | tensorflow-gpu | 2.3.3 | GHSA-2xgj-xhgf-ggjv |
| PyPI | tensorflow-gpu | 2.4.2 | GHSA-2xgj-xhgf-ggjv |
| PyPI | tensorflow-gpu | 2.1.4 | GHSA-2xgj-xhgf-ggjv |
| PyPI | tensorflow-gpu | 2.1.4, 2.2.3, 2.3.3, 2.4.2 | PYSEC-2021-738 |
| PyPI | tensorflow-gpu | 2.2.3 | GHSA-2xgj-xhgf-ggjv |
Affected products (as reported)
| Vendor | Product | Versions |
|---|---|---|
| tensorflow | tensorflow | < 2.1.4>= 2.2.0, < 2.2.3>= 2.3.0, < 2.3.3>= 2.4.0, < 2.4.2 |
Weakness: CWE-120 · Vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:L
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2xgj-xhgf-ggjv x_refsource_CONFIRM
- https://github.com/tensorflow/tensorflow/commit/0ab290774f91a23bebe30a358fde4e53ab4876a0 x_refsource_MISC
- https://github.com/tensorflow/tensorflow/commit/ba6822bd7b7324ba201a28b2f278c29a98edbef2 x_refsource_MISC