Vulnerability · Published May 14, 2021 · Assigned by GitHub_M

CVE-2021-29531CHECK-fail in tf.raw_ops.EncodePng

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. An attacker can trigger a `CHECK` fail in PNG encoding by providing an empty input tensor as the pixel data. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L57-L60) only validates that the total number of pixels in the image does not overflow. Thus, an attacker can send an empty matrix for encoding. However, if the tensor is empty, then the associated buffer is `nullptr`. Hence, when calling `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L79-L93), the first argument (i.e., `image.flat<T>().data()`) is `NULL`. This then triggers the `CHECK_NOTNULL` in the first line of `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/lib/png/png_io.cc#L345-L349). Since `image` is null, this results in `abort` being called after printing the stacktrace. Effectively, this allows an attacker to mount a denial of service attack. 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-3qxp-qjq7-w4hf
PyPItensorflow2.4.2GHSA-3qxp-qjq7-w4hf
PyPItensorflow2.1.4GHSA-3qxp-qjq7-w4hf
PyPItensorflow2.1.4, 2.2.3, 2.3.3, 2.4.2PYSEC-2021-168
PyPItensorflow2.2.3GHSA-3qxp-qjq7-w4hf
PyPItensorflow-cpu2.4.2GHSA-3qxp-qjq7-w4hf
PyPItensorflow-cpu2.1.4GHSA-3qxp-qjq7-w4hf
PyPItensorflow-cpu2.2.3GHSA-3qxp-qjq7-w4hf
PyPItensorflow-cpu2.3.3GHSA-3qxp-qjq7-w4hf
PyPItensorflow-cpu2.1.4, 2.2.3, 2.3.3, 2.4.2PYSEC-2021-459
PyPItensorflow-gpu2.3.3GHSA-3qxp-qjq7-w4hf
PyPItensorflow-gpu2.4.2GHSA-3qxp-qjq7-w4hf
PyPItensorflow-gpu2.1.4GHSA-3qxp-qjq7-w4hf
PyPItensorflow-gpu2.1.4, 2.2.3, 2.3.3, 2.4.2PYSEC-2021-657
PyPItensorflow-gpu2.2.3GHSA-3qxp-qjq7-w4hf

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-754 · Vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

References