MediumVulnerability

CVE-2022-23590: TensorFlow crash from malicious GraphDef in SavedModel

Source: NVD(opens in a new tab)
Identifier: CVE-2022-23590
Published: February 4, 2022
Record updated: October 9, 2026

Affected: tensorflow < 2.7.1
tensorflow-cpu < 2.7.1
tensorflow-gpu < 2.7.1
Fixed in: 2.7.1
tensorflow 2.7.1 released February 2, 2022, 3 days before disclosure
tensorflow-cpu 2.7.1 released February 2, 2022, 3 days before disclosure
tensorflow-gpu 2.7.1 released February 2, 2022, 3 days before disclosure
Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 1.0%

Summary

CVE-2022-23590 affects TensorFlow. A GraphDef inside a TensorFlow SavedModel can be maliciously altered so that a TensorFlow process crashes when it encounters a StatusOr value holding an error and forcibly extracts the value from it. The source says both TensorFlow 2.8.0 and TensorFlow 2.7.1 are affected.

Mitigation

Patched in multiple GitHub commits, to be included in TensorFlow 2.8.0 and TensorFlow 2.7.1.

Details

Scores and exploitation

CVSS score: 5.9(medium)
Patch available: Yes
EPSS: 1.0%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-754

Affected

Packages: tensorflow@< 2.7.1 (fixed: 2.7.1)
tensorflow-cpu@< 2.7.1 (fixed: 2.7.1)
tensorflow-gpu@< 2.7.1 (fixed: 2.7.1)
Vendors: Google

Classification

Attack type: Denial of service
Attack sophistication: Moderate
AI component targeted: Framework
Impact: 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-2022-23590

First tracked: February 15, 2026 at 08:40 PM ET, from NVD/CVE Database

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

Classifier confidence: 90% (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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