Fix(security): block unsafe pickle deserialization to mitigate CVE-2025-10164 (#11909)

Co-authored-by: Chengxing Xie <xiechengxing34@gmail.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

docs/index.rst

@@ -98,3 +98,9 @@ Its core features include:
    references/custom_chat_template.md
    references/frontend/frontend_index.rst
    references/learn_more.md
+
+.. toctree::
+   :maxdepth: 1
+   :caption: Security Acknowledgement
+
+   security/acknowledgements.md

docs/security/acknowledgements.md

+| Time       | CVE ID       | Credit to        | Affected Versions         | Severity   | Impact               | Description |
+|------------|--------------|------------------|---------------------------|------------|----------------------|-------------|
+| 2025-09-09 | CVE-2025-10164 | Simon Huang, pjf | ≥ 0.4.6 & ≤ 0.5.3          | Critical   | Remote Code Execution | A security flaw exists in lmsys sglang versions ≥ 0.4.6 and ≤ 0.5.3. The vulnerability arises from the use of unsafe pickle deserialization of the `serialized_named_tensors` parameter in the `/update_weights_from_tensor` API endpoint, which could allow a remote attacker to execute arbitrary code on the server by sending a specially crafted payload. |

python/sglang/srt/utils/common.py

@@ -2099,7 +2099,78 @@ class MultiprocessingSerializer:
             # Decode base64 string to bytes
             data = pybase64.b64decode(data, validate=True)
 
-        return ForkingPickler.loads(data)
+        class SafeUnpickler(pickle.Unpickler):
+            ALLOWED_MODULE_PREFIXES = {
+                # --- Python types ---
+                "builtins.",
+                "collections.",
+                "copyreg.",
+                "functools.",
+                "itertools.",
+                "operator.",
+                "types.",
+                "weakref.",
+                # --- PyTorch types ---
+                "torch.",
+                "torch._tensor.",
+                "torch.storage.",
+                "torch.nn.parameter.",
+                "torch.autograd.function.",
+                # --- torch distributed ---
+                "torch.distributed.",
+                "torch.distributed._shard.",
+                "torch.distributed._composable.",
+                "torch._C._distributed_c10d.",
+                "torch._C._distributed_fsdp.",
+                "torch.distributed.optim.",
+                # --- multiprocessing ---
+                "multiprocessing.resource_sharer.",
+                "multiprocessing.reduction.",
+                "pickletools.",
+                # --- PEFT / LoRA ---
+                "peft.",
+                "transformers.",
+                "huggingface_hub.",
+                # --- SGLang & Unitest ---
+                "sglang.srt.weight_sync.tensor_bucket.",
+                "sglang.srt.model_executor.model_runner.",
+                "sglang.srt.layers.",
+                "sglang.srt.utils.",
+            }
+
+            DENY_CLASSES = {
+                ("builtins", "eval"),
+                ("builtins", "exec"),
+                ("builtins", "compile"),
+                ("os", "system"),
+                ("subprocess", "Popen"),
+                ("subprocess", "run"),
+                ("codecs", "decode"),
+                ("types", "CodeType"),
+                ("types", "FunctionType"),
+            }
+
+            def find_class(self, module, name):
+                # Block deterministic attacks
+                if (module, name) in self.DENY_CLASSES:
+                    raise RuntimeError(
+                        f"Blocked unsafe class loading ({module}.{name}), "
+                        f"to prevent exploitation of CVE-2025-10164"
+                    )
+                # Allowlist of safe-to-load modules.
+                if any(
+                    (module + ".").startswith(prefix)
+                    for prefix in self.ALLOWED_MODULE_PREFIXES
+                ):
+                    return super().find_class(module, name)
+
+                # Block everything else. (Potential attack surface)
+                raise RuntimeError(
+                    f"Blocked unsafe class loading ({module}.{name}), "
+                    f"to prevent exploitation of CVE-2025-10164"
+                )
+
+        return SafeUnpickler(io.BytesIO(data)).load()
 
 
 def debug_timing(func):