Vulnerability · Published May 14, 2021 · Assigned by GitHub_M

CVE-2021-29521Segfault in SparseCountSparseOutput

Low 2.5

In plain English

A low-severity security flaw 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 0.2% (higher than 9% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.

Severity (CVSS 3.1)2.5Low
Exploit odds (30 days)0.2%top 91.4% 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. Specifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap<T>` (i.e., `std::vector<absl::flat_hash_map<int64,T>>`(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure. If the `shape` tensor has more than one element, `num_batches` is the first value in `shape`. Ensuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3.

Affected packages & fixed versions

EcosystemPackageFixed inAdvisory
PyPItensorflow2.3.3, 2.4.2PYSEC-2021-158
PyPItensorflow2.3.3GHSA-hr84-fqvp-48mm
PyPItensorflow2.4.2GHSA-hr84-fqvp-48mm
PyPItensorflow-cpu2.3.3, 2.4.2PYSEC-2021-449
PyPItensorflow-cpu2.4.2GHSA-hr84-fqvp-48mm
PyPItensorflow-cpu2.3.3GHSA-hr84-fqvp-48mm
PyPItensorflow-gpu2.3.3, 2.4.2PYSEC-2021-647
PyPItensorflow-gpu2.3.3GHSA-hr84-fqvp-48mm
PyPItensorflow-gpu2.4.2GHSA-hr84-fqvp-48mm

Affected products (as reported)

VendorProductVersions
tensorflow tensorflow < 2.3.3>= 2.4.0, < 2.4.2

Weakness: CWE-131 · Vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

References