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.

Severity (CVSS 3.1)3.6Low
Exploit odds (30 days)0.3%top 78.7% of all CVEs
Exploited in the wildNo reportsnot in CISA KEV
Attack toolingNoneno public tooling known

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

EcosystemPackageFixed inAdvisory
PyPItensorflow2.3.3GHSA-2xgj-xhgf-ggjv
PyPItensorflow2.4.2GHSA-2xgj-xhgf-ggjv
PyPItensorflow2.1.4GHSA-2xgj-xhgf-ggjv
PyPItensorflow2.1.4, 2.2.3, 2.3.3, 2.4.2PYSEC-2021-249
PyPItensorflow2.2.3GHSA-2xgj-xhgf-ggjv
PyPItensorflow-cpu2.4.2GHSA-2xgj-xhgf-ggjv
PyPItensorflow-cpu2.1.4GHSA-2xgj-xhgf-ggjv
PyPItensorflow-cpu2.2.3GHSA-2xgj-xhgf-ggjv
PyPItensorflow-cpu2.3.3GHSA-2xgj-xhgf-ggjv
PyPItensorflow-cpu2.1.4, 2.2.3, 2.3.3, 2.4.2PYSEC-2021-540
PyPItensorflow-gpu2.3.3GHSA-2xgj-xhgf-ggjv
PyPItensorflow-gpu2.4.2GHSA-2xgj-xhgf-ggjv
PyPItensorflow-gpu2.1.4GHSA-2xgj-xhgf-ggjv
PyPItensorflow-gpu2.1.4, 2.2.3, 2.3.3, 2.4.2PYSEC-2021-738
PyPItensorflow-gpu2.2.3GHSA-2xgj-xhgf-ggjv

Affected products (as reported)

VendorProductVersions
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