CVE-2026-14535
In Trail of Bits fickling versions up to and including 0.1.11, the UnsafeImportsML analysis pass unconditionally calls AnalysisContext.shorten_code(node) on every import node it inspects, regardless of whether the import is flagged as unsafe. This call registers the shortened code representation in the shared AnalysisContext.reported_shortened_code set. When the MLAllowlist analysis pass subsequently runs, it calls the same shorten_code() method, receives already_reported=True for every import, and executes a continue statement that skips its allowlist check entirely. This renders MLAllowlist dead code for all imports — it never evaluates whether an import is in the ML allowlist or not. The MLAllowlist pass was designed to catch imports of modules outside the known-safe ML ecosystem (torch, numpy, transformers, etc.) that slip past the UnsafeImports denylist. With MLAllowlist inoperative, any standard library module not in the UNSAFE_IMPORTS denylist can be invoked via pickle deserialization while fickling's check_safety() returns LIKELY_SAFE. The fickling.load() API chains check_safety() into pickle.loads() as an explicit security gate, meaning a LIKELY_SAFE verdict causes the payload to be deserialized and executed. The root cause is shared mutable state between independently-correct analysis passes — UnsafeImportsML works as designed in isolation, MLAllowlist works as designed in isolation, but the shared reported_shortened_code set causes UnsafeImportsML to poison MLAllowlist's deduplication logic.
Ce que ça veut dire
- Exposition
- Exploitable à distance depuis le réseau, sans authentification et sans action de la victime.
- Impact
- Un attaquant peut lire des données sensibles, modifier ou détruire des données et mettre le service hors ligne.
- Faiblesse
- Une protection prévue est absente ou contournable.
- Probabilité
- Le score EPSS reste bas : rien n’annonce une exploitation imminente, ce qui ne dispense pas de corriger.
À faireÀ corriger sans attendre le prochain cycle de correctifs. Commencer par les instances exposées à Internet.
Lecture automatique du vecteur CVSS, du type de faiblesse (CWE) et du score EPSS. La description technique ci-dessus reste celle publiée par le NIST, en anglais.