diff --git a/python/sglang/srt/utils/async_probe.py b/python/sglang/srt/utils/async_probe.py
index aefc63bcc..f937fd85c 100644
--- a/python/sglang/srt/utils/async_probe.py
+++ b/python/sglang/srt/utils/async_probe.py
@@ -5,30 +5,38 @@ When the gate is on, a violation surfaces as an assertion at the next CUDA
 sync point instead of as a silent NaN cascade or illegal-address crash.
 """
 
+from typing import Optional
+
 import torch
 
 from sglang.srt.environ import envs
 
 
-def maybe_detect_nan(tensor: torch.Tensor, msg: str = ""):
+def maybe_detect_nan(tensor: Optional[torch.Tensor], msg: str = ""):
     """Async NaN check — no GPU-CPU sync, error surfaces at next sync point."""
     if not envs.SGLANG_ENABLE_ASYNC_ASSERT.get():
         return
+    # A None tensor means there is nothing to probe, e.g. hidden_states on
+    # capture_hidden_mode=NULL paths (STANDALONE speculative decoding).
+    if tensor is None:
+        return
     torch._assert_async(~torch.any(torch.isnan(tensor)), f"NaN detected! {msg}")
 
 
-def maybe_detect_inf(tensor: torch.Tensor, msg: str = ""):
+def maybe_detect_inf(tensor: Optional[torch.Tensor], msg: str = ""):
     """Async Inf check — fp16 overflow surfaces as Inf before NaN."""
     if not envs.SGLANG_ENABLE_ASYNC_ASSERT.get():
         return
+    if tensor is None:
+        return
     torch._assert_async(~torch.any(torch.isinf(tensor)), f"Inf detected! {msg}")
 
 
-def maybe_detect_oob(indices: torch.Tensor, low: int, high: int, msg: str):
+def maybe_detect_oob(indices: Optional[torch.Tensor], low: int, high: int, msg: str):
     """Async OOB check — no GPU-CPU sync, error surfaces at next sync point."""
     if not envs.SGLANG_ENABLE_ASYNC_ASSERT.get():
         return
-    if indices.numel() == 0:
+    if indices is None or indices.numel() == 0:
         return
     torch._assert_async(
         (indices.min() >= low) & (indices.max() < high),
@@ -36,11 +44,13 @@ def maybe_detect_oob(indices: torch.Tensor, low: int, high: int, msg: str):
     )
 
 
-def maybe_detect_page_aligned(indices: torch.Tensor, page_size: int, msg: str):
+def maybe_detect_page_aligned(
+    indices: Optional[torch.Tensor], page_size: int, msg: str
+):
     """Async page-alignment check on slot ids."""
     if not envs.SGLANG_ENABLE_ASYNC_ASSERT.get():
         return
-    if indices.numel() == 0 or page_size <= 1:
+    if indices is None or indices.numel() == 0 or page_size <= 1:
         return
     torch._assert_async(
         (indices % page_size == 0).all(),