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CVE-2026-14666

Publié : 13 août 2026
Modifié : 13 août 2026
Lien officiel NVD
Score CVSS
4.2
MEDIUM

Description détaillée

Incomplete tracking in PostgreSQL of changes to role membership, role attributes, and database ownership allows a query to continue using cached row-level security policies after those changes require a different policy, via plan reuse. Stale policies continue until some other event invalidates the cache or connection termination ends the session. This permits a user to complete reads and modifications that were recently permitted but now forbidden. An attacker must tailor an attack to a particular application's pattern of privilege removal and role-specific row security policies. Versions before PostgreSQL 18.5, 17.11, 16.15, 15.19, and 14.24 are affected.

Vecteur d'attaque (CVSS)

Vecteur brut :CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:L/I:L/A:N

Références et Patchs

Dernières Vulnérabilités

CVE-2026-73558

vLLM is an inference and serving engine for large language models. Prior to 0.27.0, an integer overflow in blockIdx.x * 2 * d in activation_kernels.cu can cause act_and_mul_kernel to consume another batched user's input, allowing a request processed in the same inference batch to receive a partial or complete copy of another user's inference result. This issue is fixed in version 0.27.0.

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CVE-2026-73557

vLLM is an inference and serving engine for large language models. From 0.20.2rc0 until 0.26.0, safe_load_prompt_embeds in vllm/renderers/embed_utils.py uses torch.sparse.check_sparse_tensor_invariants, whose process-global save, enable, and restore state can be raced by concurrent prompt_embeds parts submitted to POST /v1/chat/completions through AsyncMultiModalItemTracker.resolve_items, asyncio.gather, and the default executor, allowing an invalid sparse tensor to reach tensor.to_dense despite the CVE-2025-62164 guard when enable_prompt_embeds is enabled. This issue is fixed in version 0.26.0.

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CVE-2026-73556

vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the structured_outputs.regex parameter in vllm/v1/structured_output/backend_lm_format_enforcer.py is passed to lmformatenforcer.RegexParser without compile_regex_with_timeout or validation in validate_structured_output_request_lm_format_enforcer, allowing an unauthenticated /v1/completions request against the lm-format-enforcer backend to consume a CPU core and stall the structured-output engine path with a catastrophic regular expression. This issue is fixed in version 0.26.0.

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