In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
This vulnerability carries a HIGH severity rating with a CVSS v3.1 score of 7.4, indicating it can be exploited remotely over the network but requires specific conditions to be met without requiring user interaction and does not require pre-existing privileges . The vulnerability impacts confidentiality (data exposure), integrity (unauthorized modifications), for affected systems. Impacting 2 products from google, from opensuse organizations running these solutions should prioritize assessment and patching.
Reported in 2020, 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.
2020-09-25T19:15:16.103
2024-11-21T05:05:05.420
Modified
CVSSv3.1: 7.4 (HIGH)
AV:N/AC:L/Au:N/C:P/I:P/A:P
10.0
6.4
| Type | Vendor | Product | Version/Range | Vulnerable? |
|---|---|---|---|---|
| Application | tensorflow | < 1.15.4 | Yes | |
| Application | tensorflow | < 2.0.3 | Yes | |
| Application | tensorflow | < 2.1.2 | Yes | |
| Application | tensorflow | < 2.2.1 | Yes | |
| Application | tensorflow | < 2.3.1 | Yes | |
| Operating System | opensuse | leap | 15.2 | 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.