HighVulnerability

CVE-2020-15207: tensorflow-lite negative index out-of-bounds access in ResolveAxis

Source: NVD(opens in a new tab)
Identifier: CVE-2020-15207
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: 1.2%

Summary

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, `ResolveAxis` converts negative axis values to positive indices, but the check that the converted index is valid exists only in debug builds, through a `DCHECK`. When that check does not trigger, execution continues with a negative index, which accesses data out of bounds and can cause segfaults or data corruption.

Mitigation

The issue is patched in commit 2d88f470dea2671b430884260f3626b1fe99830a 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: 8.7(high)
Patch available: Yes
EPSS: 1.2%Estimated probability that this CVE is exploited in the next 30 days, from the FIRST Exploit Prediction Scoring System. Read on November 3, 2026.

Weaknesses and techniques

Weakness (CWE): CWE-119
CWE-787
Attack pattern (CAPEC): CAPEC-100

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-2020-15207

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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