diff --git a/csrc/cache_kernels.cu b/csrc/cache_kernels.cu
index 0aa0dc14c7480..a6c953ee0eac9 100644
--- a/csrc/cache_kernels.cu
+++ b/csrc/cache_kernels.cu
@@ -965,7 +965,9 @@ __global__ void gather_and_maybe_dequant_cache(
     }
   };
 
-  for (int pid = split_start; pid < full_blocks_end; ++pid) {
+  const auto loop_end =
+      std::min((int64_t)full_blocks_end, block_table_stride - offset);
+  for (int pid = split_start; pid < loop_end; ++pid) {
     auto block_id = batch_block_table[pid];
     auto block_start_ptr = src_cache + block_id * cache_block_stride;
     auto block_dst_ptr = dst + pid * block_size * dst_entry_stride;
@@ -976,12 +978,15 @@ __global__ void gather_and_maybe_dequant_cache(
   }
 
   if (partial_block_size) {
-    auto block_id = batch_block_table[full_blocks_end];
-    auto block_start_ptr = src_cache + block_id * cache_block_stride;
-    auto block_dst_ptr = dst + full_blocks_end * block_size * dst_entry_stride;
-    for (int eid = 0; eid < partial_block_size; ++eid) {
-      copy_entry(block_start_ptr + eid * cache_entry_stride,
-                 block_dst_ptr + eid * dst_entry_stride);
+    if (offset + full_blocks_end < block_table_stride) {
+      auto block_id = batch_block_table[full_blocks_end];
+      auto block_start_ptr = src_cache + block_id * cache_block_stride;
+      auto block_dst_ptr =
+          dst + full_blocks_end * block_size * dst_entry_stride;
+      for (int eid = 0; eid < partial_block_size; ++eid) {
+        copy_entry(block_start_ptr + eid * cache_entry_stride,
+                   block_dst_ptr + eid * dst_entry_stride);
+      }
     }
   }
 }
diff --git a/tests/kernels/test_cache_kernels.py b/tests/kernels/test_cache_kernels.py
new file mode 100644
index 0000000000000..b5d66b4ede886
--- /dev/null
+++ b/tests/kernels/test_cache_kernels.py
@@ -0,0 +1,65 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+"""Unit tests for CUDA kernels in cache_kernels.cu."""
+
+import pytest
+import torch
+
+try:
+    from vllm import _custom_ops as ops
+except ImportError:
+    pytest.skip(
+        "Could not import vllm._custom_ops. (pip install -e .)", allow_module_level=True
+    )
+
+
+@pytest.mark.skipif(torch.cuda.device_count() < 1, reason="Need CUDA device")
+def test_gather_cache_oob():
+    """
+    Tests for OOB read in gather_and_maybe_dequant_cache (Issue #27909).
+    This test constructs a boundary case identified in the issue where
+    seq_starts causes the block_table offset to read out of bounds.
+    """
+
+    batch_size = 1
+    block_size = 64
+    entry_size = 128
+
+    block_table = torch.tensor([[1, 2]], dtype=torch.int32, device="cuda")
+
+    # This will result in offset = 128 / block_size = 128 / 64 = 2
+    # This will cause the kernel to try to read from
+    # block_table[0, 2], but its size is only 2.
+    seq_starts = torch.tensor([128], dtype=torch.int32, device="cuda")
+
+    seq_len = 65
+    cu_seq_lens = torch.tensor([0, seq_len], dtype=torch.int32, device="cuda")
+
+    # src_cache: [num_blocks, block_size, entry_size]
+    num_blocks = 5
+    src_cache = torch.randn(
+        (num_blocks, block_size, entry_size), dtype=torch.float16, device="cuda"
+    )
+
+    dst = torch.empty((seq_len, entry_size), dtype=torch.float16, device="cuda")
+
+    scale = torch.tensor([1.0], dtype=torch.float32, device="cuda")
+
+    # Calling the C++ function gather_and_maybe_dequant_cache
+    ops.gather_and_maybe_dequant_cache(
+        src_cache,
+        dst,
+        block_table,
+        cu_seq_lens,
+        batch_size,
+        "auto",  # kv_cache_dtype
+        scale,
+        seq_starts,
+    )
+
+    torch.cuda.synchronize()
+    assert True
+
+
+if __name__ == "__main__":
+    pytest.main([__file__])