feat: implement numbered patch-stack apply/verify enforcement (DGR-028)

Split the range-loader patch into single-concern patches 0002-0005 (loader,
filtered state report, boundary I/O endpoint guard, worker range-report
hook), add UPSTREAM-ASSUMPTIONS.json describing each patch's assumptions,
and enforce control-plane/license boundary checks plus first-incompatible-
patch reporting in scripts/llama_cpp_dependency.py apply/reverse/verify.

7 passed in tests/test_llama_cpp_dependency.py; SHA256SUMS verified against
all five patches; focused native CTest (test-meshnet-range-ownership 1/1)
recorded in evidence README (build/ dir not present in this environment to
independently reverify).

packages/node/native/llama/patches/0004-dense-boundary-io-endpoint-guard.patch

@@ -0,0 +1,73 @@
+From: Meshnet <meshnet@invalid>
+Subject: [PATCH] llama: guard dense graph behind boundary endpoint ownership
+
+Concern: boundary I/O. Extends the range report with endpoint ownership flags
+derived from the registered tensor map and fails the dense-Llama graph closed
+for any partial owned range until typed head/tail endpoint adapters carry the
+architecture boundary I/O.
+---
+diff --git a/include/llama.h b/include/llama.h
+index 6fd7ad509..8a7521349 100644
+--- a/include/llama.h
++++ b/include/llama.h
+@@ -300,6 +300,8 @@ extern "C" {
+         int32_t end_layer;
+         uint64_t mapped_bytes;
+         uint64_t resident_bytes;
++        bool has_token_embeddings;
++        bool has_output_head;
+     };
+ 
+     struct llama_model_params {
+diff --git a/src/llama-model.cpp b/src/llama-model.cpp
+index efb290c1f..2ea8598ad 100644
+--- a/src/llama-model.cpp
++++ b/src/llama-model.cpp
+@@ -1649,11 +1649,17 @@ bool llama_model_base::load_tensors(llama_model_loader & ml) {
+         if (ml.use_mmap) {
+             meshnet_mapped_bytes = meshnet_resident_bytes;
+         }
++        const auto registered_name = [this](const char * name) {
++            return std::any_of(tensors_by_name.begin(), tensors_by_name.end(),
++                [name](const auto & entry) { return entry.first == name; });
++        };
+         pimpl->meshnet_range_report = {
+             meshnet_start,
+             meshnet_end,
+             meshnet_mapped_bytes,
+             meshnet_resident_bytes,
++            registered_name("token_embd.weight"),
++            output_norm != nullptr && output != nullptr,
+         };
+         pimpl->has_meshnet_range_report = true;
+     }
+diff --git a/src/models/llama.cpp b/src/models/llama.cpp
+index c3092763b..3b6854d0c 100644
+--- a/src/models/llama.cpp
++++ b/src/models/llama.cpp
+@@ -108,6 +108,25 @@ std::unique_ptr<llm_graph_context> llama_model_llama::build_arch_graph(const llm
+ 
+ template <bool embed>
+ llama_model_llama::graph<embed>::graph(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) {
++    llama_meshnet_range_report meshnet_report = {};
++    if (model.meshnet_range_report(&meshnet_report)) {
++        // A partial owned range cannot execute the stock head/tail graph: the
++        // architecture boundary I/O must arrive through a typed endpoint
++        // adapter instead of local embeddings or the local output head.
++        if (meshnet_report.start_layer != 0) {
++            throw std::runtime_error("Meshnet dense-Llama graph requires a head endpoint adapter");
++        }
++        if (meshnet_report.end_layer != n_layer) {
++            throw std::runtime_error("Meshnet dense-Llama graph requires a tail endpoint adapter");
++        }
++        if (!meshnet_report.has_token_embeddings) {
++            throw std::runtime_error("Meshnet dense-Llama head range is missing token embeddings");
++        }
++        if (!meshnet_report.has_output_head) {
++            throw std::runtime_error("Meshnet dense-Llama tail range is missing final norm or output head");
++        }
++    }
++
+     const int64_t n_embd_head = hparams.n_embd_head_v();
+ 
+     GGML_ASSERT(n_embd_head == hparams.n_embd_head_k());