Vulnerability · Published Sep 25, 2020 · Assigned by GitHub_M

CVE-2020-15201Heap buffer overflow in Tensorflow

Medium 4.8

In plain English

A medium-severity improper input validation 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 0.6% (higher than 47% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.

Severity (CVSS 3.1)4.8Medium
Exploit odds (30 days)0.6%top 52.7% of all CVEs
Exploited in the wildNo reportsnot in CISA KEV
Attack toolingNoneno public tooling known

Official description

In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Hence, the code is prone to heap buffer overflow. If `split_values` does not end with a value at least `num_values` then the `while` loop condition will trigger a read outside of the bounds of `split_values` once `batch_idx` grows too large. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

Affected packages & fixed versions

EcosystemPackageFixed inAdvisory
PyPItensorflow2.3.1GHSA-p5f8-gfw5-33w4
PyPItensorflow2.3.1PYSEC-2020-124
PyPItensorflow-cpu2.3.1GHSA-p5f8-gfw5-33w4
PyPItensorflow-cpu2.3.1PYSEC-2020-281
PyPItensorflow-gpu2.3.1GHSA-p5f8-gfw5-33w4
PyPItensorflow-gpu2.3.1PYSEC-2020-316

Affected products (as reported)

VendorProductVersions
tensorflow tensorflow = 2.3.0

Weakness: CWE-20, CWE-122 · Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:N

References