diff --git a/ext/ComponentArraysMooncakeExt.jl b/ext/ComponentArraysMooncakeExt.jl
index 60d51cce..a7a5de8f 100644
--- a/ext/ComponentArraysMooncakeExt.jl
+++ b/ext/ComponentArraysMooncakeExt.jl
@@ -1,16 +1,113 @@
 module ComponentArraysMooncakeExt
 
 using ComponentArrays, Mooncake
+using Base: IEEEFloat
 
-# ComponentVector handling in @from_rrule
+const _FloatLike = Union{IEEEFloat, Complex{<:IEEEFloat}}
+
+# === Flat-Array-backed ComponentVector fdata ==========================================
+# `Mooncake.FData{@NamedTuple{data::A, axes::NoFData}}` is the fdata layout of a
+# `ComponentArray{T, N, A<:Array, Axes}` — the common "owns its storage" case.
+#
+# We need to handle three incoming ChainRules cotangent shapes that arise from
+# `@from_rrule` / `@from_chainrules` declarations:
+#   (a) a raw `Array{P}` matching the primal underlying storage,
+#   (b) a `ComponentArray` with the same underlying storage type,
+#   (c) a `ComponentArray` whose data field is a different `AbstractArray{P}`
+#       (e.g. a `SubArray` produced by projecting a parent cotangent).
+
+# (a) raw Array cotangent
 function Mooncake.increment_and_get_rdata!(
         f::Mooncake.FData{@NamedTuple{data::A, axes::Mooncake.NoFData}},
         r::Mooncake.NoRData,
         t::A,
-    ) where {P <: Union{Base.IEEEFloat, Complex{<:Base.IEEEFloat}}, A <: Array{P}}
+    ) where {P <: _FloatLike, A <: Array{P}}
     return Mooncake.increment_and_get_rdata!(f.data[:data], r, t)
 end
 
+# (b) / (c) ComponentArray cotangent against a flat-Array-backed primal
+function Mooncake.increment_and_get_rdata!(
+        f::Mooncake.FData{@NamedTuple{data::A, axes::Mooncake.NoFData}},
+        r::Mooncake.NoRData,
+        t::ComponentArray{P, N, <:AbstractArray{P}},
+    ) where {P <: _FloatLike, N, A <: Array{P}}
+    data_t = getdata(t)
+    t_vec = data_t isa Array{P} ? data_t : collect(data_t)
+    return Mooncake.increment_and_get_rdata!(f.data[:data], r, t_vec)
+end
+
+# === SubArray-backed ComponentVector fdata ============================================
+# A `ComponentVector` produced by `getproperty(::ComponentVector, ::Symbol)` (and any
+# other view-producing path) wraps a `SubArray` rather than a `Vector`. Its Mooncake
+# fdata accordingly nests an inner `FData` describing the SubArray's fields.
+#
+# We can only aggregate a ChainRules cotangent into this layout when the view fully
+# covers its parent — otherwise the unmodelled indices leave us unable to place the
+# cotangent into the correct slice of the parent tangent. That "full cover" case is
+# however the common one: sub-CVs that land at an `@from_rrule` boundary are usually
+# freshly allocated and own all of their parent storage. Outside of that, we raise a
+# clear error instead of silently corrupting gradients.
+
+function _increment_subarray_fdata!(f_cv, t_data::AbstractArray{P}) where {P <: _FloatLike}
+    parent = f_cv.data[:data].data[:parent]
+    if length(t_data) != length(parent)
+        throw(
+            ArgumentError(
+                "ComponentArraysMooncakeExt: cannot aggregate a cotangent of length " *
+                "$(length(t_data)) into a SubArray-backed ComponentVector tangent whose " *
+                "parent has length $(length(parent)). This happens when a cotangent " *
+                "flows into a view that does not fully cover its parent; there is no " *
+                "way to recover the view indices from Mooncake fdata alone. Please " *
+                "file an issue against ComponentArrays.jl with a reproducer so the " *
+                "offending rrule can be patched.",
+            ),
+        )
+    end
+    t_vec = t_data isa Array{P} ? t_data : collect(t_data)
+    Mooncake.increment_and_get_rdata!(parent, Mooncake.NoRData(), t_vec)
+    return Mooncake.NoRData()
+end
+
+function Mooncake.increment_and_get_rdata!(
+        f::Mooncake.FData{
+            @NamedTuple{
+                data::Mooncake.FData{
+                    @NamedTuple{
+                        parent::Array{P, 1},
+                        indices::Mooncake.NoFData,
+                        offset1::Mooncake.NoFData,
+                        stride1::Mooncake.NoFData,
+                    },
+                },
+                axes::Mooncake.NoFData,
+            },
+        },
+        r::Mooncake.NoRData,
+        t::Array{P},
+    ) where {P <: _FloatLike}
+    return _increment_subarray_fdata!(f, t)
+end
+
+function Mooncake.increment_and_get_rdata!(
+        f::Mooncake.FData{
+            @NamedTuple{
+                data::Mooncake.FData{
+                    @NamedTuple{
+                        parent::Array{P, 1},
+                        indices::Mooncake.NoFData,
+                        offset1::Mooncake.NoFData,
+                        stride1::Mooncake.NoFData,
+                    },
+                },
+                axes::Mooncake.NoFData,
+            },
+        },
+        r::Mooncake.NoRData,
+        t::ComponentArray{P, N, <:AbstractArray{P}},
+    ) where {P <: _FloatLike, N}
+    return _increment_subarray_fdata!(f, getdata(t))
+end
+
 function Mooncake.friendly_tangent_cache(x::ComponentArray)
     Mooncake.FriendlyTangentCache{Mooncake.AsPrimal}(copy(x))
 end
diff --git a/test/autodiff/Project.toml b/test/autodiff/Project.toml
index cec53860..0d382e23 100644
--- a/test/autodiff/Project.toml
+++ b/test/autodiff/Project.toml
@@ -1,8 +1,10 @@
 [deps]
 ArrayInterface = "4fba245c-0d91-5ea0-9b3e-6abc04ee57a9"
+ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 ComponentArrays = "b0b7db55-cfe3-40fc-9ded-d10e2dbeff66"
 FiniteDiff = "6a86dc24-6348-571c-b903-95158fe2bd41"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
+Mooncake = "da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"
 Optimisers = "3bd65402-5787-11e9-1adc-39752487f4e2"
 ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
@@ -11,8 +13,10 @@ Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [compat]
 ArrayInterface = "7.22.0"
+ChainRulesCore = "1"
 FiniteDiff = "2.29.0"
 ForwardDiff = "1.3.1"
+Mooncake = "0.5.26"
 Optimisers = "0.4.7"
 ReverseDiff = "1.16.2"
 Tracker = "0.2.38"
diff --git a/test/autodiff/autodiff_tests.jl b/test/autodiff/autodiff_tests.jl
index 119b6e9c..d412abac 100644
--- a/test/autodiff/autodiff_tests.jl
+++ b/test/autodiff/autodiff_tests.jl
@@ -1,5 +1,5 @@
 using ComponentArrays
-import FiniteDiff, ForwardDiff, ReverseDiff, Tracker, Zygote
+import ChainRulesCore, FiniteDiff, ForwardDiff, Mooncake, ReverseDiff, Tracker, Zygote
 using Optimisers, ArrayInterface
 using Test
 
@@ -134,3 +134,74 @@ end
     @test ArrayInterface.restructure(ps, ps_tracked) isa
         ComponentVector{<:Any, <:Tracker.TrackedArray}
 end
+
+@testset "Mooncake" begin
+    # Native Mooncake rules — gradient through `getproperty` on a flat ComponentVector
+    # and on a ComponentVector with nested axes.
+    flat = ComponentArray(a = 1.0, b = 2.0, c = 3.0)
+    loss_flat(p) = sum(abs2, p.a) + 0.5 * p.b + p.c^2
+    let
+        cache = Mooncake.prepare_gradient_cache(loss_flat, flat)
+        _, g = Mooncake.value_and_gradient!!(cache, loss_flat, flat)
+        @test g[2].fields.data ≈ [2.0, 0.5, 6.0]
+    end
+
+    u0 = ComponentArray(x = 1.0, y = 2.0)
+    p_all = ComponentArray(a = 3.0, b = 4.0, c = 5.0)
+    nested = ComponentArray(; u0, p_all)
+    loss_nested(θ) = sum(abs2, θ.u0) + 0.5 * sum(abs2, θ.p_all)
+    let
+        cache = Mooncake.prepare_gradient_cache(loss_nested, nested)
+        _, g = Mooncake.value_and_gradient!!(cache, loss_nested, nested)
+        @test g[2].fields.data ≈ [2.0, 4.0, 3.0, 4.0, 5.0]
+    end
+
+    # @from_rrule round-trip — this is the path that fails without the extension,
+    # because ComponentArrays' `ChainRulesCore.rrule` for `getdata`/`getproperty`/
+    # `Type{ComponentArray}(...)` returns `ComponentArray` cotangents that Mooncake's
+    # `increment_and_get_rdata!` dispatch rejects by default. Downstream SciML
+    # packages hit this whenever they declare an `@from_rrule` with a ComponentArray
+    # argument, which is how the SciMLSensitivity tutorials exercised it.
+    sum_abs2(x::AbstractArray) = sum(abs2, x)
+    function ChainRulesCore.rrule(::typeof(sum_abs2), x::AbstractArray)
+        y = sum_abs2(x)
+        function sum_abs2_pb(Δy)
+            return (
+                ChainRulesCore.NoTangent(),
+                ComponentArray(2 .* Δy .* getdata(x), getaxes(x)),
+            )
+        end
+        return y, sum_abs2_pb
+    end
+    function ChainRulesCore.rrule(::typeof(sum_abs2), x::AbstractVector)
+        y = sum_abs2(x)
+        sum_abs2_pb(Δy) = (ChainRulesCore.NoTangent(), 2 .* Δy .* x)
+        return y, sum_abs2_pb
+    end
+    Mooncake.@from_rrule(
+        Mooncake.DefaultCtx,
+        Tuple{typeof(sum_abs2), ComponentVector{Float64, Vector{Float64}}},
+    )
+
+    # (a) ComponentArray cotangent against a flat-Array-backed CV fdata
+    let
+        v = ComponentArray(a = 1.0, b = 2.0, c = 3.0)
+        cache = Mooncake.prepare_gradient_cache(sum_abs2, v)
+        val, g = Mooncake.value_and_gradient!!(cache, sum_abs2, v)
+        @test val ≈ 14.0
+        @test g[2].fields.data ≈ [2.0, 4.0, 6.0]
+    end
+
+    # (b) Nested ComponentArray constructed with `ComponentArray(; u0, p_all)`
+    #     — the "feedback_control.md" layout from SciMLSensitivity#1419.
+    let
+        nested2 = ComponentArray(; u0 = [1.0, 2.0], p_all = ComponentArray(a = 3.0, b = 4.0))
+        cache = Mooncake.prepare_gradient_cache(sum_abs2, nested2)
+        val, g = Mooncake.value_and_gradient!!(cache, sum_abs2, nested2)
+        @test val ≈ 30.0
+        @test g[2].fields.data ≈ [2.0, 4.0, 6.0, 8.0]
+    end
+
+    @test Mooncake.friendly_tangent_cache(flat) isa
+        Mooncake.FriendlyTangentCache{Mooncake.AsPrimal}
+end