Vulnerability Monitor

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CVE-2020-15201


In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Hence, the code is prone to heap buffer overflow. If `split_values` does not end with a value at least `num_values` then the `while` loop condition will trigger a read outside of the bounds of `split_values` once `batch_idx` grows too large. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.


Security Impact Summary

This vulnerability carries a MEDIUM severity rating with a CVSS v3.1 score of 4.8, 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 limited data confidentiality, limited integrity, for affected systems. Impacting 1 product from google organizations running these solutions should prioritize assessment and patching.

Historical Context

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.


Published

2020-09-25T19:15:15.353

Last Modified

2026-06-17T02:56:15.237

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 4.8 (MEDIUM)

CVSSv2 Vector

AV:N/AC:M/Au:N/C:P/I:P/A:P

  • Access Vector: NETWORK
  • Access Complexity: MEDIUM
  • Authentication: NONE
  • Confidentiality Impact: PARTIAL
  • Integrity Impact: PARTIAL
  • Availability Impact: PARTIAL
Exploitability Score

8.6

Impact Score

6.4

Weaknesses
  • Type: Secondary
    CWE-20
    CWE-122
  • Type: Primary
    CWE-787

Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application google tensorflow 2.3.0 Yes

References

How SecUtils Interprets This CVE

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.