HighVulnerability

CVE-2026-62997: Kedro-Datasets PyTorchDataset code execution via unsafe torch.load

Source: NVD(opens in a new tab)
Identifier: CVE-2026-62997
Published: September 16, 2026
Record updated: October 9, 2026

Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 0.7%

Summary

Kedro-Datasets versions 5.0.0 through 9.5.0 have a flaw in kedro_datasets_experimental.pytorch.PyTorchDataset, which loads .pt model files with torch.load without enforcing weights_only=True and silently drops user-supplied load_args. On PyTorch versions earlier than 2.6, a malicious pickle-backed model from an attacker-influenced source can execute arbitrary code when a Kedro pipeline loads it. The issue affects only the opt-in experimental component.

Mitigation

Fixed in version 9.5.0.

Details

Scores and exploitation

EPSS: 0.7%Estimated probability that this CVE is exploited in the next 30 days, from the FIRST Exploit Prediction Scoring System. Read on November 4, 2026.
Disclosure date: September 16, 2026

Weaknesses and techniques

Weakness (CWE): CWE-502
Attack pattern (CAPEC): CAPEC-586
AI threat technique (MITRE ATLAS): AML.T0010

Classification

Attack type: Supply chain
Attack sophistication: Moderate
AI component targeted: Training data
Impact: Integrity,
Availability,
Confidentiality
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-2026-62997

First tracked: September 16, 2026 at 08:07 PM ET, from NVD/CVE Database

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

Classifier confidence: 90% (self-assessed)

Summary

Mitigation

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