HighVulnerability

CVE-2020-25459: WeBank FATE sync_tree exposes sensitive data during joint modeling training

Source: NVD(opens in a new tab)
Identifier: CVE-2020-25459
Published: June 16, 2022
Record updated: October 9, 2026

Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 1.0%

Summary

CVE-2020-25459 affects the sync_tree function in hetero_decision_tree_guest.py in WeBank FATE (Federated AI Technology Enabler) versions 0.1 through 1.4.2. The flaw allows attackers to read sensitive information during the training process of machine learning joint modeling. The weakness is classified as CWE-668, Exposure of Resource to Wrong Sphere.

Mitigation

The source references a patch in the FATE repository commit 6feccf6d752184a6f9365d56a76fe627983e7139, but does not describe the fix itself.

Details

Scores and exploitation

CVSS score: 7.5(high)
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-668

Classification

Attack type: Data extraction
Attack sophistication: Moderate
AI component targeted: Framework
Impact: Confidentiality
Labels: security,
privacy

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-2020-25459

First tracked: February 15, 2026 at 08:53 PM ET, from NVD/CVE Database

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

Classifier confidence: 90% (self-assessed)

Summary

Mitigation

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