HighVulnerability

CVE-2026-14535: Trail of Bits fickling MLAllowlist bypass allows unsafe pickle deserialization

Source: NVD(opens in a new tab)
Identifier: CVE-2026-14535
Published: July 4, 2026
Record updated: October 9, 2026

Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 0.6%

Summary

In Trail of Bits fickling versions up to and including 0.1.11, the UnsafeImportsML pass calls AnalysisContext.shorten_code(node) on every import, which marks each import as already reported in the shared reported_shortened_code set. The MLAllowlist pass then receives already_reported=True for every import and skips its allowlist check, so standard library modules outside the UNSAFE_IMPORTS denylist can pass check_safety() as LIKELY_SAFE. Because fickling.load() passes that verdict to pickle.loads(), such a payload is deserialized and executed.

Mitigation

The source does not state a fix yet. Check the original advisory for updates.

Details

Scores and exploitation

CVSS score: 8.8(high)
CVSS vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Attack vector: network
Attack complexity: low
Privileges required: none
User interaction: required
EPSS: 0.6%Estimated probability that this CVE is exploited in the next 30 days, from the FIRST Exploit Prediction Scoring System. Read on October 11, 2026.
Disclosure date: July 4, 2026

Weaknesses and techniques

Weakness (CWE): CWE-693

Classification

Attack type: Other
Attack sophistication: Moderate
AI component targeted: Framework
Impact: Confidentiality,
Integrity
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-2026-14535

First tracked: July 4, 2026 at 02:07 PM ET, from NVD/CVE Database

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

Classifier confidence: 90% (self-assessed)

Summary

Mitigation

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