CVE-2026-47623
Description détaillée
NVIDIA Dynamo for Linux contains a vulnerability where an attacker could cause deserialization of untrusted data. A successful exploit of this vulnerability might lead to denial of service and data tampering.
Vecteur d'attaque (CVSS)
Dernières Vulnérabilités
CVE-2026-70474
Flowise is a drag-and-drop user interface for building customized large language model (LLM) flows. Prior to 3.1.3, Flowise has three OAuth2 credential endpoints that look up credentials by id alone with no workspaceId filter. The authorize, callback, and refresh handlers query the Credential table by id only; callback and refresh are whitelisted from authentication. This allows any authenticated user to initiate OAuth2 flows against credentials belonging to other workspaces, allows an unauthenticated attacker to forge OAuth2 callbacks to overwrite tokens in any credential, and allows an unauthenticated attacker to refresh tokens for any credential. The affected routes include /api/v1/oauth2-credential/authorize/<VICTIM_CREDENTIAL_UUID>, /api/v1/oauth2-credential/callback?code=ATTACKER_AUTH_CODE&state=<VICTIM_CREDENTIAL_UUID>, and /api/v1/oauth2-credential/refresh/<VICTIM_CREDENTIAL_UUID>. This issue is fixed in version 3.1.3.
CVE-2026-70473
Flowise is a drag-and-drop user interface for building customized large language model (LLM) flows. Prior to 3.1.3, Flowise GET /api/v1/upsert-history returns the entire server-wide upsert history instead of being scoped to the requesting user, tenant, or workspace. The response can exceed 100MB and includes sensitive configuration data, including Vector Store settings such as Qdrant Server URL and collection name. The observed behavior indicates missing or insufficient authorization checks, workspace/project/tenant isolation, and pagination or limits, exposing integration parameters and infrastructure details that may enable further targeted attacks. This issue is fixed in version 3.1.3.
CVE-2026-70472
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, Flowise openai-assistants-vector-store endpoints accept a client-controlled credential parameter and load credentials by id without checking whether that credential belongs to the caller workspace. Route permissions assistants:* only check feature access. The controller passes req.query.credential straight to the service, and the service uses findOneBy({ id: credentialId }), decrypts the credential, and calls OpenAI APIs without a workspaceId check. If an attacker knows another workspace credentialId, the attacker can use that workspace OpenAI key, read, modify, or delete victim vector stores and files, cause billing impact on the victim OpenAI account, and violate multi-tenant boundaries. This issue is fixed in version 3.1.3.