tannevaled · Oct 12, 2026 · Oct 11, 2026
diff --git a/README.md b/README.md
@@ -19,7 +19,7 @@ describes**:
 
 | Source | Published under |
 | --- | --- |
-| branch `main`, with `params.ndarray.version: v0.11.0` in `hugo.yaml` | `https://go-ndarray.github.io/docs/<MAJOR.MINOR>/`, here `/docs/0.11/` |
+| branch `main`, with `params.ndarray.version: v0.12.0` in `hugo.yaml` | `https://go-ndarray.github.io/docs/<MAJOR.MINOR>/`, here `/docs/0.12/` |
 | the newest version | also `https://go-ndarray.github.io/docs/latest/` |
 
 `https://go-ndarray.github.io/docs/` redirects to `latest/`. Each push to

diff --git a/content/en/_index.md b/content/en/_index.md
@@ -47,7 +47,7 @@ WebAssembly, with nothing to install — build a pipeline step by step (creation
 | Linear algebra | `MatMul`, `Dot`, `Inner`, `Outer`; package `linalg` ([page](linalg.md)): `Solve`, `Inv`, `Det`, `Slogdet`, `Cholesky`, `QR`, `SVD`, `Eigh`, `Eig`, `Lstsq`, `Pinv`, `MatrixRank`, `Norm`, `Cond`, `MatrixPower`, `MultiDot` |
 | Fourier transforms | package `fft`: `numpy.fft` on arrays (`FFT`/`RFFT`/`FFT2`/`FFTN`/… with `n`/`s`, `axes`, `norm`), over [go-fft](https://github.com/go-fft/fft) |
 | Random numbers | package `random` ([page](random.md)): PCG64, PCG64DXSM, MT19937, Philox, SFC64; `Generator` (`DefaultRNG`, 40 samplers) and the legacy `RandomState` (`Seed`, `Rand`) |
-| Notebooks & storage | `Repr` (prints like NumPy), `Display` (text and HTML), `MarshalBinary`/`UnmarshalBinary` (the same bytes on every architecture) |
+| Notebooks & storage | `Repr` (character for character what NumPy 2.5.3's `repr` prints, checked against NumPy's own test strings), `Display` (text and HTML), `MarshalBinary`/`UnmarshalBinary` (the same bytes on every architecture) |
 | Memory reuse | `NewWorkspace`, `Use`, `Reset`, `Detach` |
 
 ## Goroutines (v0.6.0)

diff --git a/content/en/dtypes.md b/content/en/dtypes.md
@@ -8,7 +8,7 @@ description: "Why the dtype is a run-time property of one Array type, how arrays
 tags: [dtypes, numpy]
 ---
 
-> Mirrored from [`docs/design-dtypes.md`](https://github.com/go-ndarray/ndarray/blob/v0.11.0/docs/design-dtypes.md) at v0.11.0.
+> Mirrored from [`docs/design-dtypes.md`](https://github.com/go-ndarray/ndarray/blob/v0.12.0/docs/design-dtypes.md) at v0.12.0.
 
 > Status: implemented (Phase 2). Supersedes decision 4 of
 > [plan-ndarray.md](roadmap.md) ("`float64` first").

diff --git a/content/en/linalg.md b/content/en/linalg.md
@@ -8,9 +8,9 @@ description: "Solve, Inv, Det, Cholesky, QR, SVD, Eig and the rest of numpy.lina
 tags: [linalg, numpy]
 ---
 
-> Mirrored from [`docs/linalg.md`](https://github.com/go-ndarray/ndarray/blob/v0.11.0/docs/linalg.md) at v0.11.0.
+> Mirrored from [`docs/linalg.md`](https://github.com/go-ndarray/ndarray/blob/v0.12.0/docs/linalg.md) at v0.12.0.
 
-Package [`linalg`](https://pkg.go.dev/github.com/go-ndarray/ndarray@v0.11.0/linalg) gives ndarray arrays the functions of
+Package [`linalg`](https://pkg.go.dev/github.com/go-ndarray/ndarray@v0.12.0/linalg) gives ndarray arrays the functions of
 `numpy.linalg`, written in Go without cgo or assembly of its own: the
 matrix products it relies on are the ndarray package's packed SIMD GEMM.
 

diff --git a/content/en/random.md b/content/en/random.md
@@ -8,9 +8,9 @@ description: "numpy.random with NumPy's numbers for the same seed: the bit gener
 tags: [random, numpy]
 ---
 
-> Mirrored from [`docs/random.md`](https://github.com/go-ndarray/ndarray/blob/v0.11.0/docs/random.md) at v0.11.0.
+> Mirrored from [`docs/random.md`](https://github.com/go-ndarray/ndarray/blob/v0.12.0/docs/random.md) at v0.12.0.
 
-Package [`random`](https://pkg.go.dev/github.com/go-ndarray/ndarray@v0.11.0/random) is `numpy.random` over go-ndarray arrays. Its goal
+Package [`random`](https://pkg.go.dev/github.com/go-ndarray/ndarray@v0.12.0/random) is `numpy.random` over go-ndarray arrays. Its goal
 is migration: a notebook moved from NumPy to Go keeps its numbers for the same
 seed.
 
@@ -24,7 +24,7 @@ u, _ := random.Rand(3)                // np.random.rand(3)
 ```
 
 `Example`, `ExampleSeed` and `ExampleGenerator_ChoiceN` in
-[`example_test.go`](https://github.com/go-ndarray/ndarray/blob/v0.11.0/random/example_test.go) print NumPy's own numbers.
+[`example_test.go`](https://github.com/go-ndarray/ndarray/blob/v0.12.0/random/example_test.go) print NumPy's own numbers.
 
 ## What is implemented
 
@@ -118,7 +118,7 @@ random arguments. Used as-is, that made 3% of `np.random.randn` values and
 10% of `lognormal` values one ULP off.
 
 So `random` rounds `log`, `log1p`, `exp`, `expm1` and `pow` **correctly**
-([`libm.go`](https://github.com/go-ndarray/ndarray/blob/v0.11.0/random/libm.go)): a fast evaluation to about 2⁻⁶⁸ with Ziv's
+([`libm.go`](https://github.com/go-ndarray/ndarray/blob/v0.12.0/random/libm.go)): a fast evaluation to about 2⁻⁶⁸ with Ziv's
 rounding test, and a double-double fallback (about 2⁻¹⁰⁰) for the one argument
 in ~2¹⁵ that needs it. Checked against mpmath at 300 bits on 63,000 arguments
 (0 misrounded; the committed `libm.json` keeps 8,400), and the fast paths

diff --git a/content/en/roadmap.md b/content/en/roadmap.md
@@ -8,7 +8,7 @@ description: "The plan for go-ndarray and what ships today."
 tags: [roadmap]
 ---
 
-> Mirrored from [`docs/plan-ndarray.md`](https://github.com/go-ndarray/ndarray/blob/v0.11.0/docs/plan-ndarray.md) at v0.11.0.
+> Mirrored from [`docs/plan-ndarray.md`](https://github.com/go-ndarray/ndarray/blob/v0.12.0/docs/plan-ndarray.md) at v0.12.0.
 
 > Goal: a **pure-Go (CGO=0)** NumPy-style N-dimensional array library, as a
 > **standalone, reusable** module with correct scalar kernels now and a clean
@@ -112,7 +112,7 @@ suite (plus the per-arch CI jobs already wired in `.github/workflows/ci.yml`).
 - **Performance — DONE (beats NumPy on its core ops; matmul at tuned-BLAS
   parity).** Several levers behind the kernel seam, measured honestly vs NumPy
   2.2.4 (see [docs/perf.md](performance.md) and the repo's
-  [BENCHMARKS.md](https://github.com/go-ndarray/ndarray/blob/v0.11.0/BENCHMARKS.md)):
+  [BENCHMARKS.md](https://github.com/go-ndarray/ndarray/blob/v0.12.0/BENCHMARKS.md)):
   - **Multicore.** `Add/Sub/Mul/Div/Map`, `Sum/Max/Min`, the axis reductions,
     `Concatenate`/`Stack`, and the GEMM fan out across `GOMAXPROCS` above a size
     threshold (small arrays stay serial). Plus an allocation fix: the

diff --git a/content/en/security.md b/content/en/security.md
@@ -8,7 +8,7 @@ description: "How to report a vulnerability, what the library guarantees, and th
 tags: [security]
 ---
 
-> Mirrored from [`SECURITY.md`](https://github.com/go-ndarray/ndarray/blob/main/SECURITY.md) at v0.11.0.
+> Mirrored from [`SECURITY.md`](https://github.com/go-ndarray/ndarray/blob/main/SECURITY.md) at v0.12.0.
 
 ## Reporting
 
@@ -61,12 +61,30 @@ bounds checks do not cover, so they are held to the following:
   test from NumPy's definitions (Python's `slice.indices`, the broadcasting
   rule, ...). The library must reject exactly the calls the oracle rejects and
   never panic.
+- **Decoding takes bytes from anywhere.** `UnmarshalBinary` refuses, with an
+  error wrapping `ErrFormat`, any input whose shape the bytes that follow do
+  not account for exactly, before it allocates; an array it accepts holds no
+  more than it was given. `FuzzUnmarshalBinary` ([`marshal_fuzz_test.go`](https://github.com/go-ndarray/ndarray/blob/main/marshal_fuzz_test.go))
+  requires that, that it never panics, and that re-encoding is a fixed point.
 
 The minimum Go version (`go` in `go.mod`) is kept on a release that fixes the
 standard library's known vulnerabilities; `govulncheck ./...` reports none.
 
 ## Audit log
 
+**2026-10-11 (after v0.11.0, tests only).** v0.10.0 added `UnmarshalBinary`,
+whose input may come from a file, a notebook or the network; no entry covered
+it. It checks the magic and the dtype, bounds the rank at 64 and each
+dimension at `maxSize`, validates the shape, and compares the data length with
+the element count by dividing, not multiplying, so a `complex128` shape cannot
+overflow the comparison. Only then does it allocate, so the allocation is the
+size of the input. `FuzzUnmarshalBinary` holds it to that, never panicking
+and re-encoding to a fixed point. It ran 11 million inputs on an M-series Mac
+with no failure. A copy that accepted fewer bytes than the shape needs failed
+it in 0.09 s (6 bytes decoded as 48 bools), so the fuzzer can see the defect
+it guards against. `govulncheck ./...` at go1.27.2 with go-fft v0.23.0 reports
+none.
+
 **2026-10-09 (v0.9.1).** New s390x `maxVXE`/`minVXE` kernels, gated on
 AT_HWCAP VXRS_EXT (z14 and later), each behind its wrapper: from eight
 elements up, with no pointer arithmetic beyond `len(a)`. On the real z17 they

diff --git a/hugo.yaml b/hugo.yaml
@@ -6,7 +6,7 @@
 # have used since the site was built with MkDocs and mike. The CI sets it
 # through --baseURL, from params.ndarray.version below. This default is the
 # same build.
-baseURL: "https://go-ndarray.github.io/docs/0.11/"
+baseURL: "https://go-ndarray.github.io/docs/0.12/"
 title: "go-ndarray"
 # themes/hextra is the tannevaled/hextra fork, pinned at a release tag:
 # upstream Hextra plus opt-in features (partial menu items, combos,
@@ -97,7 +97,7 @@ params:
   # The ndarray release these pages describe. Its minor version is the
   # documentation's version label (v0.9.1 -> 0.9): the CI reads it here.
   ndarray:
-    version: "v0.11.0"
+    version: "v0.12.0"
 
   navbar:
     displayTitle: true