AVID-2026-R0964

Description

Integer overflow in TFLite (CVE-2022-23559)

Details

Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause an integer overflow in embedding lookup operations. Both embedding_size and lookup_size are products of values provided by the user. Hence, a malicious user could trigger overflows in the multiplication. In certain scenarios, this can then result in heap OOB read/write. Users are advised to upgrade to a patched version.

Reason for inclusion in AVID: CVE-2022-23559 describes an integer overflow in TFLite embedding_lookup_sparse that can cause heap OOB read/write. This is a software vulnerability in a widely-used ML framework (TensorFlow/TFLite) affecting AI/ML systems. The issue involves a library/component used to build/run general-purpose AI systems (embedding lookup, model inference) and pertains to the software supply chain (dependencies/frameworks). The report provides CVE details, severity (HIGH), and references, offering clear evidence.

References

• NVD entry
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-98p5-x8x4-c9m5
• https://github.com/tensorflow/tensorflow/commit/1de49725a5fc4e48f1a3b902ec3599ee99283043
• https://github.com/tensorflow/tensorflow/commit/a4e401da71458d253b05e41f28637b65baf64be4
• https://github.com/tensorflow/tensorflow/commit/f19be71717c497723ba0cea0379e84f061a75e01
• https://github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/kernels/embedding_lookup_sparse.cc#L179-L189

Affected or Relevant Artifacts

• Developer: tensorflow
• Deployer: tensorflow
• Artifact Details:

Impact

AVID Taxonomy Categorization

• Risk domains: Security
• SEP subcategories: S0100: Software Vulnerability
• Lifecycle stages: L06: Deployment

CVSS

CWE

Other information

• Report Type: Advisory
• Credits:
• Date Reported: 2022-02-04
• Version: 0.3.3
• AVID Entry