tools: plugin: ov_noise_suppression: validate model input shape dimensions

noise_suppression_load_model() and noise_suppression_first_iter() take
the input tensor shape directly from the OpenVINO model file via
nd->model->input(...).get_shape() and feed the resulting dimensions
into downstream size computations and allocations without any range
check.

A crafted or corrupted .xml/.bin model can specify dimensions that are
either zero (producing zero-sized allocations later written into) or
large enough that a subsequent multiplication overflows before being
used as a buffer length. Both lead to out-of-bounds memory access at
inference time. The same pattern exists for the per-iteration input
state shape, which is also read from the model.

After fetching each shape, walk its dimensions and reject the model
with -EINVAL if any dimension is zero or exceeds 1 << 24 (16 Mi
elements). The upper bound is well above any realistic noise
suppression tensor dimension and well below the point at which a
product of two such dimensions can overflow a 32-bit size on the
platforms this plugin targets, which closes the integer-overflow path
without rejecting valid models.

No functional change for well-formed models; malformed models now fail
the load instead of corrupting memory.

Reported-by: OrbisAI Security scanner (V-004, CWE-190)
Signed-off-by: OrbisAI Security <mediratta01.pally@gmail.com>

Author: orbisai0security

tools/plugin/modules/ov_noise_suppression/noise_suppression_interface.cpp

@@ -85,6 +85,9 @@ extern "C" {
 			nd->infer_request[i] = compiled_model.create_infer_request();
 
 		nd->inp_shape = nd->model->input("input").get_shape();
+		for (auto dim : nd->inp_shape)
+			if (!dim || dim > (1u << 24))
+				return -EINVAL;
 
 		return 0;
 	}
@@ -141,6 +144,9 @@ extern "C" {
 				ov::Shape state_shape;
 
 				state_shape = nd->model->input(inp_state_name).get_shape();
+				for (auto dim : state_shape)
+					if (!dim || dim > (1u << 24))
+						return -EINVAL;
 				if (nd->iter > 0) {
 					/*
 					 * set input state by corresponding output state from prev