HighVulnerability

CVE-2020-15208: tensorflow-lite out-of-bounds read and write from tensor dimension check

Source: NVD(opens in a new tab)
Identifier: CVE-2020-15208
Published: September 25, 2020
Record updated: October 10, 2026

Affected: tensorflow < 1.15.4, fixed in 1.15.4, released September 24, 2020, 1 day before disclosure
tensorflow >= 2.0.0, < 2.0.3, fixed in 2.0.3, released September 24, 2020, 1 day before disclosure
tensorflow >= 2.1.0, < 2.1.2, fixed in 2.1.2, released September 24, 2020, 1 day before disclosure
and 12 more
Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 0.9%

Summary

TensorFlow Lite versions before 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1 determine the common dimension size of two tensors with a DCHECK that is a no-op outside debug builds, and the function always returns the first tensor's dimension. An attacker can craft tensors where that value exceeds the second tensor's, causing out-of-bounds reads and writes because the interpreter assumes both tensors hold enough data.

Mitigation

The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d and released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Details

Scores and exploitation

CVSS score: 7.4(high)
Patch available: Yes
EPSS: 0.9%Estimated probability that this CVE is exploited in the next 30 days, from the FIRST Exploit Prediction Scoring System. Read on November 4, 2026.

Weaknesses and techniques

Weakness (CWE): CWE-125
CWE-787
Attack pattern (CAPEC): CAPEC-100
CAPEC-540

Affected

Packages: tensorflow@< 1.15.4 (fixed: 1.15.4)
tensorflow@>= 2.0.0, < 2.0.3 (fixed: 2.0.3)
tensorflow@>= 2.1.0, < 2.1.2 (fixed: 2.1.2)
tensorflow@= 2.2.0 (fixed: 2.2.1)
tensorflow@= 2.3.0 (fixed: 2.3.1)
tensorflow-cpu@< 1.15.4 (fixed: 1.15.4)
tensorflow-cpu@>= 2.0.0, < 2.0.3 (fixed: 2.0.3)
tensorflow-cpu@>= 2.1.0, < 2.1.2 (fixed: 2.1.2)
tensorflow-cpu@= 2.2.0 (fixed: 2.2.1)
tensorflow-cpu@= 2.3.0 (fixed: 2.3.1)
tensorflow-gpu@< 1.15.4 (fixed: 1.15.4)
tensorflow-gpu@>= 2.0.0, < 2.0.3 (fixed: 2.0.3)
tensorflow-gpu@>= 2.1.0, < 2.1.2 (fixed: 2.1.2)
tensorflow-gpu@= 2.2.0 (fixed: 2.2.1)
tensorflow-gpu@= 2.3.0 (fixed: 2.3.1)
Vendors: Google

Classification

Attack type: Other
Attack sophistication: Moderate
AI component targeted: Framework
Impact: Confidentiality,
Integrity,
Availability
Labels: security

How this record was produced

Summaries, mitigations and labels on this page are generated automatically from the source. The linked source is authoritative. The source gives this advisory a description and no title, so the title above is a headline generated from the source text.

Original source: https://nvd.nist.gov/vuln/detail/CVE-2020-15208

First tracked: February 15, 2026 at 08:38 PM ET, from NVD/CVE Database

Classifier: claude-haiku-5-5, prompt v4

Classifier confidence: 95% (self-assessed)

Affected packages in the Exposure Registry

Matched by package name and ecosystem. Each entry shows whether the package delegates to a language model and how many tracked packages depend on it.

tensorflowPyPINo LLM dependency detected · 26 tracked dependents
tensorflow-gpuPyPINo LLM dependency detected · 2 tracked dependents

Summary

Mitigation

Affected packages in the Exposure Registry

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