An out-of-bounds write issue was addressed with improved bounds checking. This issue is fixed in macOS Golden Gate 27.2. Mounting a maliciously crafted disk image may cause unexpected system termination or corrupt kernel memory.
A race condition was addressed with improved locking. This issue is fixed in macOS Golden Gate 27.2, macOS Sequoia 15.8.2, macOS Tahoe 26.7.2. An app may be able to cause unexpected system termination or corrupt process memory.
An out-of-bounds write issue was addressed with improved bounds checking. This issue is fixed in macOS Golden Gate 27.2. Mounting a malicious disk image may cause unexpected system termination.
This issue was addressed with improved file handling. This issue is fixed in macOS Golden Gate 27.2, macOS Sequoia 15.8.2, macOS Tahoe 26.7.2. A malicious application may be able to execute arbitrary code with system privileges.
A buffer overflow was addressed with improved bounds checking. This issue is fixed in macOS Golden Gate 27.2, macOS Sequoia 15.8.2, macOS Tahoe 26.7.2. Processing a maliciously crafted image may lead to unexpected process termination.
A double free issue was addressed with improved memory management. This issue is fixed in macOS Golden Gate 27.2, macOS Sequoia 15.8.2, macOS Tahoe 26.7.2. An attacker on the local network may be able to cause unexpected system termination or corrupt process memory.
A logic issue was addressed with improved state management. This issue is fixed in macOS Golden Gate 27.2, macOS Sequoia 15.8.2, macOS Tahoe 26.7.2. An unprivileged attacker may be able to execute arbitrary code as root.
An authentication issue was addressed with improved state management. This issue is fixed in macOS Golden Gate 27.2. A remote attacker may be able to cause arbitrary code execution.
vLLM is an inference and serving engine for large language models. From 0.16.0 until 0.32.0, the /v1/responses endpoint allows an authenticated caller to place an attacker-controlled template in chat_template_kwargs[chat_template] when no server template is configured. ChatParams.get_apply_chat_template_kwargs() preserves that value without enforcing trust_request_chat_template, so the request can bypass the intended trust policy and cause CPU or memory exhaustion through Jinja rendering. This issue is fixed in version 0.32.0.
vLLM is an inference and serving engine for large language models. From 0.11.1 until 0.32.0, the DeepSeek-OCR, DeepSeek-OCR-2, and Unlimited-OCR image path allows a remote client that can reach the OpenAI-compatible API to submit a legal image whose normalized pixels sum to zero when that image is alone in its per-step encoder batch. _parse_and_validate_image_input returns no embedding, embed_multimodal propagates that value, and sanity_check_mm_encoder_outputs triggers a fatal assertion that shuts down the engine for all users. This issue is fixed in version 0.32.0.