TensorFlow is an end-to-end open source platform for machine learning. In affected versions if the arguments to `tf.raw_ops.RaggedGather` don't determine a valid ragged tensor code can trigger a read from outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/ragged_gather_op.cc#L70) directly reads the first dimension of a tensor shape before checking that said tensor has rank of at least 1 (i.e., it is not a scalar). Furthermore, the implementation does not check that the list given by `params_nested_splits` is not an empty list of tensors. We have patched the issue in GitHub commit a2b743f6017d7b97af1fe49087ae15f0ac634373. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
This vulnerability carries a HIGH severity rating with a CVSS v3.1 score of 7.3, requiring local system access to exploit with relatively low complexity without requiring user interaction requiring only low-level privileges . The vulnerability impacts confidentiality (data exposure), limited integrity, and availability (service disruption) for affected systems. Impacting 1 product from google organizations running these solutions should prioritize assessment and patching.
Reported in 2021, this vulnerability emerged during an era marked by increased sophistication in supply chain attacks, cloud infrastructure vulnerabilities, and software-as-a-service (SaaS) security challenges. Security practices during this period emphasized zero-trust architectures, container security, and API protection.
2021-08-12T21:15:07.670
2026-06-17T04:00:53.273
Modified
CVSSv3.1: 7.3 (HIGH)
AV:L/AC:L/Au:N/C:P/I:N/A:P
3.9
4.9
| Type | Vendor | Product | Version/Range | Vulnerable? |
|---|---|---|---|---|
| Application | tensorflow | < 2.3.4 | Yes | |
| Application | tensorflow | < 2.4.3 | Yes | |
| Application | tensorflow | 2.5.0 | Yes | |
| Application | tensorflow | 2.6.0 | Yes | |
| Application | tensorflow | 2.6.0 | Yes | |
| Application | tensorflow | 2.6.0 | Yes |
SecUtils normalizes and enriches National Vulnerability Database (NVD) records by standardizing vendor and product identifiers, aggregating vulnerability metadata from both NVD and MITRE sources, and providing structured context for security teams. For google's affected products, we extract Common Platform Enumeration (CPE) data, Common Weakness Enumeration (CWE) classifications, CVSS severity metrics, and reference data to enable rapid vulnerability prioritization and asset correlation. This record contains no exploit code, proof-of-concept instructions, or attack methodologies—only defensive intelligence necessary for patch management, risk assessment, and security operations.