diff --git a/lib/DiffEqBase/ext/DiffEqBaseEnzymeExt.jl b/lib/DiffEqBase/ext/DiffEqBaseEnzymeExt.jl
index c3f69716c08..8a0f7d4bfa5 100644
--- a/lib/DiffEqBase/ext/DiffEqBaseEnzymeExt.jl
+++ b/lib/DiffEqBase/ext/DiffEqBaseEnzymeExt.jl
@@ -114,6 +114,7 @@ module DiffEqBaseEnzymeExt
             # `sensealg` is inactive (see augmented_primal note); skip its slot
             # whether it arrived as Const or as a runtime-activity-promoted
             # Duplicated/MixedDuplicated/Active.
+            rta = Enzyme.EnzymeRules.runtime_activity(config) # detect runtime activity
             for (darg, ptr) in zip(dargs, (func, prob, sensealg, u0, p, args...))
                 if ptr isa Enzyme.Const
                     continue
@@ -124,9 +125,18 @@ module DiffEqBaseEnzymeExt
                 if darg == ChainRulesCore.NoTangent()
                     continue
                 end
+                # Under `set_runtime_activity` (detected by rta), a runtime-inactive value arrives as
+                # Duplicated/MixedDuplicated with its shadow ALIASING the primal
+                # (`dval === val`). Accumulating the cotangent into such a shadow writes
+                # gradient values into the caller's primal data (e.g. the `u0` of a
+                # `Const` problem whose array was reused via `remake`), silently
+                # corrupting subsequent calls. Skip them: a runtime-inactive value
+                # accumulates nowhere, exactly as if it were `Const`.
                 if ptr isa MixedDuplicated
+                    rta && ptr.dval[] === ptr.val && continue
                     _accumulate_tangent!(ptr.dval[], darg)
                 else
+                    rta && ptr.dval === ptr.val && continue
                     _accumulate_tangent!(ptr.dval, darg)
                 end
             end
diff --git a/lib/DiffEqBase/test/downstream/Project.toml b/lib/DiffEqBase/test/downstream/Project.toml
index 3183685d3bf..d1b907b8c2a 100644
--- a/lib/DiffEqBase/test/downstream/Project.toml
+++ b/lib/DiffEqBase/test/downstream/Project.toml
@@ -4,6 +4,7 @@ DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 DiffEqBase = "2b5f629d-d688-5b77-993f-72d75c75574e"
 DiffEqCallbacks = "459566f4-90b8-5000-8ac3-15dfb0a30def"
 DifferentiationInterface = "a0c0ee7d-e4b9-4e03-894e-1c5f64a51d63"
+Enzyme = "7da242da-08ed-463a-9acd-ee780be4f1d9"
 FlexUnits = "76e01b6b-c995-4ce6-8559-91e72a3d4e95"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 GTPSA = "b27dd330-f138-47c5-815b-40db9dd9b6e8"
@@ -21,6 +22,7 @@ OrdinaryDiffEqSymplecticRK = "fa646aed-7ef9-47eb-84c4-9443fc8cbfa8"
 OrdinaryDiffEqVerner = "79d7bb75-1356-48c1-b8c0-6832512096c2"
 SDEProblemLibrary = "c72e72a9-a271-4b2b-8966-303ed956772e"
 SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
+SciMLSensitivity = "1ed8b502-d754-442c-8d5d-10ac956f44a1"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 StochasticDiffEq = "789caeaf-c7a9-5a7d-9973-96adeb23e2a0"
 SymbolicIndexingInterface = "2efcf032-c050-4f8e-a9bb-153293bab1f5"
@@ -41,8 +43,10 @@ StochasticDiffEq = {path = "../../../StochasticDiffEq"}
 [compat]
 ADTypes = "1"
 DifferentiationInterface = "0.7"
+Enzyme = "0.13.100"
 ForwardDiff = "0.10, 1"
 GTPSA = "1.4"
 MultiScaleArrays = "1.8"
 OrdinaryDiffEq = "7"
+SciMLSensitivity = "7"
 StochasticDiffEq = "7"
diff --git a/lib/DiffEqBase/test/downstream/enzyme_solve_up_rule.jl b/lib/DiffEqBase/test/downstream/enzyme_solve_up_rule.jl
new file mode 100644
index 00000000000..8e887f59c0d
--- /dev/null
+++ b/lib/DiffEqBase/test/downstream/enzyme_solve_up_rule.jl
@@ -0,0 +1,57 @@
+# Regression test for the DiffEqBaseEnzymeExt `solve_up` reverse rule guard
+# (SciML/OrdinaryDiffEq.jl#3740): under `set_runtime_activity`, a u0 that aliases a
+# Const-annotated problem's own array must not receive the du0 cotangent (its
+# "shadow" IS the primal). First gradient call used to be correct while silently
+# corrupting `prob.u0`; the second call then returned garbage.
+#
+# Deps: SciMLSensitivity (real adjoint), OrdinaryDiffEqVerner, Enzyme, ForwardDiff.
+
+using DiffEqBase, Enzyme, Test
+using SciMLSensitivity
+using OrdinaryDiffEqVerner
+using ForwardDiff
+
+f_oop(u, p, t) = p .* u
+u0_init = [2.0, 3.0]
+p_init = [0.5, 0.7]
+prob = ODEProblem(f_oop, copy(u0_init), (0.0, 1.0), copy(p_init))
+
+solve_kwargs = (; saveat = 0.25, abstol = 1.0e-8, reltol = 1.0e-8)
+
+@testset "runtime-activity aliased u0 is not corrupted" begin
+    # u0 is the Const problem's own array reused via remake — the
+    # `setsym_oop`/`remake` pattern of MTK loss functions.
+    function loss_aliased(p, q)
+        prob = q[1]
+        prob2 = remake(prob; u0 = prob.u0, p = p)
+        sol = solve(prob2, Vern7(); sensealg = GaussAdjoint(), solve_kwargs...)
+        return sum(abs2, Array(sol))
+    end
+
+    q = (prob,)
+    g_ref = ForwardDiff.gradient(p -> loss_aliased(p, q), p_init)
+
+    g1 = Enzyme.gradient(set_runtime_activity(Enzyme.Reverse), loss_aliased, copy(p_init), Const(q))[1]
+    @test g1 ≈ g_ref rtol = 1.0e-5
+    @test prob.u0 == u0_init     # primal problem must NOT have been mutated
+    g2 = Enzyme.gradient(set_runtime_activity(Enzyme.Reverse), loss_aliased, copy(p_init), Const(q))[1]
+    @test g2 ≈ g_ref rtol = 1.0e-5 # second call sees uncorrupted state
+end
+
+@testset "genuinely active u0 still accumulates" begin
+    # The guard must not skip accumulation when a real shadow exists: here both
+    # u0 and p derive from the differentiated input, so du0 must flow.
+    function loss_active(x, q)
+        prob2 = remake(q[1]; u0 = x[1:2], p = x[3:4])
+        sol = solve(prob2, Vern7(); sensealg = GaussAdjoint(), solve_kwargs...)
+        return sum(abs2, Array(sol))
+    end
+
+    q = (prob,)
+    x0 = vcat(u0_init, p_init)
+    g_ref = ForwardDiff.gradient(x -> loss_active(x, q), x0)
+    @test maximum(abs, g_ref[1:2]) > 0  # sanity: u0 gradient is nonzero
+
+    g = Enzyme.gradient(set_runtime_activity(Enzyme.Reverse), loss_active, copy(x0), Const(q))[1]
+    @test g ≈ g_ref rtol = 1.0e-5
+end
diff --git a/lib/DiffEqBase/test/runtests.jl b/lib/DiffEqBase/test/runtests.jl
index b1a9f02f074..faf829e8b90 100644
--- a/lib/DiffEqBase/test/runtests.jl
+++ b/lib/DiffEqBase/test/runtests.jl
@@ -81,6 +81,12 @@ end
         @time @safetestset "LabelledArrays Tests" include("downstream/labelledarrays.jl")
         @time @safetestset "GTPSA Tests" include("downstream/gtpsa.jl")
         @time @safetestset "SubArray Support" include("downstream/subarray_support.jl")
+        # Run ahead of the Unitful/FlexUnits tests: a @safetestset that errors
+        # (FlexUnits currently does) aborts the rest of this group, which would
+        # otherwise shadow this test. DiffEqBaseEnzymeExt is disabled on prerelease.
+        if isempty(VERSION.prerelease)
+            @time @safetestset "Enzyme solve_up rule" include("downstream/enzyme_solve_up_rule.jl")
+        end
         @time @safetestset "Unitful" include("downstream/unitful.jl")
         @time @safetestset "FlexUnits" include("downstream/flexunits.jl")
     end