Description
Tensorflow is an Open Source Machine Learning Framework. When decoding PNG images TensorFlow can produce a memory leak if the image is invalid. After calling `png::CommonInitDecode(..., &decode)`, the `decode` value contains allocated buffers which can only be freed by calling `png::CommonFreeDecode(&decode)`. However, several error case in the function implementation invoke the `OP_REQUIRES` macro which immediately terminates the execution of the function, without allowing for the memory free to occur. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Understanding This Vulnerability
This Common Vulnerabilities and Exposures (CVE) entry provides detailed information about a security vulnerability that has been publicly disclosed. CVEs are standardized identifiers assigned by MITRE Corporation to track and catalog security vulnerabilities across software and hardware products.
The severity rating (MEDIUM) indicates the potential impact of this vulnerability based on the CVSS (Common Vulnerability Scoring System) framework. Higher severity ratings typically indicate vulnerabilities that could lead to more significant security breaches if exploited. Security teams should prioritize remediation efforts based on severity, exploit availability, and the EPSS (Exploit Prediction Scoring System) score, which predicts the likelihood of exploitation in the wild.
If this vulnerability affects products or systems in your infrastructure, we recommend reviewing the affected products section, checking for available patches or updates from vendors, and implementing recommended workarounds or solutions until a permanent fix is available. Organizations should also monitor security advisories and threat intelligence feeds for updates about active exploitation of this vulnerability.