Описание
A flaw was found in pydantic-ai. A remote attacker could exploit this vulnerability by submitting crafted message history containing unvalidated file references. This could trick the server into reading arbitrary files from its own cloud storage accounts, such as Amazon S3 or Google Cloud Storage, or from other tenants. The primary consequence is information disclosure, potentially exposing sensitive data.
Затронутые пакеты
| Платформа | Пакет | Состояние | Рекомендация | Релиз |
|---|---|---|---|---|
| Lightspeed Core | lightspeed-core/lightspeed-stack-rhel9 | Not affected | ||
| Red Hat Enterprise Linux AI (RHEL AI) 3 | rhelai3/bootc-cuda-rhel9 | Not affected | ||
| Red Hat Enterprise Linux AI (RHEL AI) 3 | rhelai3/bootc-gaudi-rhel9 | Not affected | ||
| Red Hat Enterprise Linux AI (RHEL AI) 3 | rhelai3/bootc-rocm-rhel9 | Not affected | ||
| Red Hat Enterprise Linux AI (RHEL AI) 3 | rhelai3/disk-image-cuda-rhel9 | Not affected |
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Дополнительная информация
Статус:
EPSS
6.8 Medium
CVSS3
Связанные уязвимости
Pydantic AI is a Python agent framework for building Generative AI applications. In versions 1.65.0 through 1.105.0, and 2.0.0b1 through 2.0.0b5, a client that submits message history to a Pydantic AI UI adapter (such as the Vercel AI adapter) can reference arbitrary files in the application's model-provider or cloud-storage account. While file URL parts are validated against a scheme allowlist, UploadedFile references — which point to a file by provider file ID or cloud-storage URI (e.g. s3://…, gs://…) — were forwarded without validation. Because the provider resolves an UploadedFile using the server-side identity (IAM role, service account, or provider API key) rather than the client's, an attacker can craft message history to make the server read objects from its own account or other tenants, given a referenceable identifier. Exploitation requires a valid file identifier, which is not always unguessable depending on how the application names objects. This issue has been fix
EPSS
6.8 Medium
CVSS3