Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 2.10.0 until 2.53.0, streamed requests made through ConcurrencyLimitedModel or limit_model_concurrency can retain shared concurrency slots because anyio.CapacityLimiter associates an acquired slot with the borrowing task while streaming cleanup can run in a different task. Early stream termination, cancellation, consumer exceptions, or complete stream_text() consumption with debounce_by=0.1 can therefore leave capacity occupied, eventually preventing later requests that share the long-lived limiter from proceeding and causing a denial of service. Agent-level max_concurrency and non-streaming model requests are not affected. This issue is fixed in version 2.53.0.
| Métrique | Valeur | Interprétation |
|---|---|---|
|
AV (Vecteur d'Attaque)
Attack Vector
|
Network (N)
|
Exploit possible à distance via réseau (HTTP, API, etc.) |
|
AC (Complexité d'Attaque)
Attack Complexity
|
Low (L)
|
Peu de conditions requises pour exploiter |
|
PR (Privilèges Requis)
Privileges Required
|
None (N)
|
Aucune authentification requise |
|
UI (Interaction Utilisateur)
User Interaction
|
None (N)
|
Aucune interaction utilisateur nécessaire |
|
S (Périmètre)
Scope
|
Unchanged (U)
|
Impact reste dans le périmètre du composant compromis |
|
C (Impact Confidentialité)
Confidentiality Impact
|
None (N)
|
Aucune divulgation d'informations |
|
I (Impact Intégrité)
Integrity Impact
|
None (N)
|
Aucune modification de données possible |
|
A (Impact Disponibilité)
Availability Impact
|
High (H)
|
Interruption totale du service possible |
Pydantic AI: Concurrency-limited models can keep their slot when a streamed request ends early
Pydantic AI: Concurrency-limited models can keep their slot when a streamed request ends early