CVE-2026-34159 llama.cpp: Unauthenticated RCE via GRAPH_COMPUTE buffer=0 bypass in llama.cpp RPC backend

llama.cpp is an inference of several LLM models in C/C++. Prior to version b8492, the RPC backend's deserializetensor skips all bounds validation when a tensor's buffer field is 0. An unauthenticated attacker can read and write arbitrary process memory via crafted GRAPHCOMPUTE messages. Combined...

CVE-2026-34159

The CVE-2026-34159 entry for llama.cpp describes an unauthenticated RCE via the RPC backend: prior to v.b8492, deserialize_tensor() omits bounds validation when tensor.buffer == 0, enabling an attacker to read/write arbitrary process memory through crafted GRAPH_COMPUTE messages. Combined with AL...

CVE-2026-34159 llama.cpp: Unauthenticated RCE via GRAPH_COMPUTE buffer=0 bypass in llama.cpp RPC backend

llama.cpp is an inference of several LLM models in C/C++. Prior to version b8492, the RPC backend's deserializetensor skips all bounds validation when a tensor's buffer field is 0. An unauthenticated attacker can read and write arbitrary process memory via crafted GRAPHCOMPUTE messages. Combined...

CVE-2026-34159

llama.cpp is an inference of several LLM models in C/C++. Prior to version b8492, the RPC backend's deserializetensor skips all bounds validation when a tensor's buffer field is 0. An unauthenticated attacker can read and write arbitrary process memory via crafted GRAPHCOMPUTE messages. Combined...

CVE-2026-34159

llama.cpp is an inference of several LLM models in C/C++. Prior to version b8492, the RPC backend's deserializetensor skips all bounds validation when a tensor's buffer field is 0. An unauthenticated attacker can read and write arbitrary process memory via crafted GRAPHCOMPUTE messages. Combined...

llama.cpp 缓冲区错误漏洞

Llama.cpp is a multimodal model developed by Georgi Gerganov. Prior versions of llama.cpp b8492 contained a buffer error vulnerability. This vulnerability stemmed from the deserializetensor function in the RPC backend, which skipped all boundary verifications when the buffer field of the tensor w...

EUVD-2025-209086

A flaw was found in Red Hat OpenShift AI RHOAI llama-stack-operator. This vulnerability allows unauthorized access to Llama Stack services deployed in other namespaces via direct network requests, because no NetworkPolicy restricts access to the llama-stack service endpoint. As a result, a user i...

CVE-2025-12805

A flaw was found in Red Hat OpenShift AI RHOAI llama-stack-operator. This vulnerability allows unauthorized access to Llama Stack services deployed in other namespaces via direct network requests, because no NetworkPolicy restricts access to the llama-stack service endpoint. As a result, a user i...

CVE-2025-12805 Llama-stack-k8s-operator: llama stack service exposed across namespaces due to missing networkpolicy

A flaw was found in Red Hat OpenShift AI RHOAI llama-stack-operator. This vulnerability allows unauthorized access to Llama Stack services deployed in other namespaces via direct network requests, because no NetworkPolicy restricts access to the llama-stack service endpoint. As a result, a user i...

CVE-2025-12805 Llama-stack-k8s-operator: llama stack service exposed across namespaces due to missing networkpolicy

A flaw was found in Red Hat OpenShift AI RHOAI llama-stack-operator. This vulnerability allows unauthorized access to Llama Stack services deployed in other namespaces via direct network requests, because no NetworkPolicy restricts access to the llama-stack service endpoint. As a result, a user i...

CVE-2025-12805

CVE-2025-12805 describes a flaw in Red Hat OpenShift AI (RHOAI) llama-stack-operator where Llama Stack services deployed in different namespaces can be accessed via direct network requests because no NetworkPolicy restricts the llama-stack service endpoint. This allows a user in one namespace to ...

CVE-2025-12805

A flaw was found in Red Hat OpenShift AI RHOAI llama-stack-operator. This vulnerability allows unauthorized access to Llama Stack services deployed in other namespaces via direct network requests, because no NetworkPolicy restricts access to the llama-stack service endpoint. As a result, a user i...

PT-2026-28270

A flaw was found in Red Hat OpenShift AI RHOAI llama-stack-operator. This vulnerability allows unauthorized access to Llama Stack services deployed in other namespaces via direct network requests, because no NetworkPolicy restricts access to the llama-stack service endpoint. As a result, a user i...

Llama Stack 安全漏洞

Llama Stack is a core building block for simplified artificial intelligence application development, open-sourced by Meta Llama. There is a security vulnerability in Llama Stack, which stems from the lack of network policy restrictions on access to the llama-stack server endpoints. This...

SUSE CVE-2026-33298

llama.cpp is an inference of several LLM models in C/C++. Prior to b7824, an integer overflow vulnerability in the ggmlnbytes function allows an attacker to bypass memory validation by crafting a GGUF file with specific tensor dimensions. This causes ggmlnbytes to return a significantly smaller...

UBUNTU-CVE-2026-33298

llama.cpp is an inference of several LLM models in C/C++. Prior to b7824, an integer overflow vulnerability in the ggmlnbytes function allows an attacker to bypass memory validation by crafting a GGUF file with specific tensor dimensions. This causes ggmlnbytes to return a significantly smaller...

CVE-2026-33298 llama.cpp has a Heap Buffer Overflow via Integer Overflow in GGUF Tensor Parsing

llama.cpp is an inference of several LLM models in C/C++. Prior to b7824, an integer overflow vulnerability in the ggmlnbytes function allows an attacker to bypass memory validation by crafting a GGUF file with specific tensor dimensions. This causes ggmlnbytes to return a significantly smaller...

CVE-2026-33298 llama.cpp has a Heap Buffer Overflow via Integer Overflow in GGUF Tensor Parsing

llama.cpp is an inference of several LLM models in C/C++. Prior to b7824, an integer overflow vulnerability in the ggmlnbytes function allows an attacker to bypass memory validation by crafting a GGUF file with specific tensor dimensions. This causes ggmlnbytes to return a significantly smaller...

CVE-2026-33298

llama.cpp is an inference of several LLM models in C/C++. Prior to b7824, an integer overflow vulnerability in the ggmlnbytes function allows an attacker to bypass memory validation by crafting a GGUF file with specific tensor dimensions. This causes ggmlnbytes to return a significantly smaller...

CVE-2026-33298

Summary (CVE-2026-33298) : llama.cpp (C/C++) contains an integer overflow in the ggml_nbytes function during GGUF tensor parsing, allowing an attacker to bypass memory validation by crafting tensor dimensions. This can cause ggml_nbytes to report a far too small size (examples cite 4 MB vs exabyt...