AVID-2026-R0751

Description

CHECK-fail in CTCGreedyDecoder (CVE-2021-29543)

Details

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a CHECK-fail in tf.raw_ops.CTCGreedyDecoder. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1615440b17b364b875eb06f43d087381f1460a65/tensorflow/core/kernels/ctc_decoder_ops.cc#L37-L50) has a CHECK_LT inserted to validate some invariants. When this condition is false, the program aborts, instead of returning a valid error to the user. This abnormal termination can be weaponized in denial of service attacks. 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.

Reason for inclusion in AVID: CVE-2021-29543 describes a CHECK failure in TensorFlow’s CTCGreedyDecoder that can be triggered to cause a denial of service. This is a software vulnerability in a widely used AI framework, directly impacting the software stack used to build, train, and deploy general-purpose AI systems. It concerns a dependency (TensorFlow) in the AI supply chain and is not hardware/firmware only. Therefore it is relevant for AVID curation as a software supply-chain vulnerability in AI systems.

References

• NVD entry
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fphq-gw9m-ghrv
• https://github.com/tensorflow/tensorflow/commit/ea3b43e98c32c97b35d52b4c66f9107452ca8fb2

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: 2021-05-14
• Version: 0.3.3
• AVID Entry