TensorFlow is an end-to-end open source platform for machine learning. In affected versions all TFLite operations that use quantization can be made to use unitialized values. [For example](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/depthwise_conv.cc#L198-L200). The issue stems from the fact that `quantization.params` is only valid if `quantization.type` is different that `kTfLiteNoQuantization`. However, these checks are missing in large parts of the code. We have patched the issue in GitHub commits 537bc7c723439b9194a358f64d871dd326c18887, 4a91f2069f7145aab6ba2d8cfe41be8a110c18a5 and 8933b8a21280696ab119b63263babdb54c298538. 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 MEDIUM severity rating with a CVSS v3.1 score of 4.4, requiring local system access to exploit with relatively low complexity without requiring user interaction requiring only low-level privileges . The vulnerability impacts limited integrity, and limited availability 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.
2021-08-12T23:15:08.390
2026-06-17T04:00:58.533
Modified
CVSSv3.1: 4.4 (MEDIUM)
AV:L/AC:L/Au:N/C:N/I:P/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.