diff --git a/lib/Dialect/TritonInstrument/Transforms/FpSanitizer.cpp b/lib/Dialect/TritonInstrument/Transforms/FpSanitizer.cpp
index c9068da03e12..047c51b9dca3 100644
--- a/lib/Dialect/TritonInstrument/Transforms/FpSanitizer.cpp
+++ b/lib/Dialect/TritonInstrument/Transforms/FpSanitizer.cpp
@@ -95,6 +95,11 @@ struct ScratchInfo {
   RankedTensorType tensorType;
 };
 
+struct ScratchState {
+  std::optional<ScratchInfo> canonical;
+  DenseMap<Region *, ScratchInfo> byScope;
+};
+
 class TmemScratchManager {
 public:
   ttg::BlockedEncodingAttr getScratchEncoding(PatternRewriter &rewriter,
@@ -143,14 +148,19 @@ class TmemScratchManager {
     }
 
     if (auto alloc = memdesc.getDefiningOp<ttng::TMEMAllocOp>()) {
-      auto it = scratchMap.find(memdesc);
-      if (it != scratchMap.end()) {
-        auto itRegion = it->second.find(scope);
-        if (itRegion != it->second.end()) {
-          if (itRegion->second.ptr && itRegion->second.ptr.getType())
-            return itRegion->second;
-          it->second.erase(itRegion);
-        }
+      ScratchState &state = scratchMap[memdesc];
+      auto itRegion = state.byScope.find(scope);
+      if (itRegion != state.byScope.end()) {
+        if (itRegion->second.ptr && itRegion->second.ptr.getType())
+          return itRegion->second;
+        state.byScope.erase(itRegion);
+      }
+      if (state.canonical) {
+        Value ptr =
+            remapToScope(state.canonical->ptr, rewriter, scope, alloc.getLoc());
+        ScratchInfo info{ptr, state.canonical->tensorType};
+        state.byScope[scope] = info;
+        return info;
       }
 
       OpBuilder::InsertionGuard guard(rewriter);
@@ -176,10 +186,11 @@ class TmemScratchManager {
           return std::nullopt;
       }
 
-      ptr = remapToScope(ptr, rewriter, scope, loc);
+      state.canonical = ScratchInfo{ptr, tensorTy};
 
+      ptr = remapToScope(ptr, rewriter, scope, loc);
       ScratchInfo info{ptr, tensorTy};
-      scratchMap[memdesc][scope] = info;
+      state.byScope[scope] = info;
       return info;
     }
 
@@ -303,7 +314,7 @@ class TmemScratchManager {
     return scope->getArgument(captureIdx);
   }
 
-  DenseMap<Value, DenseMap<Region *, ScratchInfo>> scratchMap;
+  DenseMap<Value, ScratchState> scratchMap;
 };
 
 Value createScratchAndStore(PatternRewriter &rewriter, Location loc, Value val,
diff --git a/python/test/gluon/test_fpsan.py b/python/test/gluon/test_fpsan.py
index 3b73ab30a99d..8fc432b8b180 100644
--- a/python/test/gluon/test_fpsan.py
+++ b/python/test/gluon/test_fpsan.py
@@ -1609,6 +1609,53 @@ def kernel(x_ptr, out_ptr):
     _assert_payload_equal(out, exp_bits)
 
 
+@pytest.mark.skipif(not is_blackwell(), reason="Requires Blackwell")
+def test_tmem_store_in_warp_specialize_partition_visible_to_parent(device, fresh_knobs):
+    _require_cuda_backend(device)
+
+    B = 64
+    BLOCK = gl.constexpr(B)
+
+    fresh_knobs.compilation.instrumentation_mode = "fpsan"
+
+    @gluon.jit
+    def store_one_partition(tmem):
+        reg_layout: gl.constexpr = tmem.get_reg_layout()
+        one = gl.full((BLOCK, BLOCK), 1.0, gl.float32, reg_layout)
+        tmem.store(one)
+
+    @gluon.jit
+    def default_partition():
+        pass
+
+    @gluon.jit
+    def kernel(out_ptr):
+        layout: gl.constexpr = gl.BlockedLayout([1, 1], [32, 1], [gl.num_warps(), 1], [1, 0])
+        offs_m = gl.arange(0, BLOCK, layout=gl.SliceLayout(1, layout))[:, None]
+        offs_n = gl.arange(0, BLOCK, layout=gl.SliceLayout(0, layout))[None, :]
+        offs = offs_m * BLOCK + offs_n
+
+        tmem_layout: gl.constexpr = TensorMemoryLayout((BLOCK, BLOCK), col_stride=1)
+        tmem = allocate_tensor_memory(gl.float32, [BLOCK, BLOCK], layout=tmem_layout)
+        reg_layout: gl.constexpr = tmem.get_reg_layout()
+        zero = gl.full((BLOCK, BLOCK), 0.0, gl.float32, reg_layout)
+        tmem.store(zero)
+
+        gl.warp_specialize([
+            (default_partition, ()),
+            (store_one_partition, (tmem, )),
+        ], [4], [32])
+
+        out = tmem.load()
+        out = gl.convert_layout(out, layout)
+        gl.store(out_ptr + offs, out)
+
+    out = torch.empty((B, B), device=device, dtype=torch.float32)
+    kernel[(1, )](out, num_warps=4)
+
+    torch.testing.assert_close(out, torch.ones_like(out), rtol=0, atol=0)
+
+
 def test_reduction(device, fresh_knobs):
     _require_cuda_backend(device)