feat: text.anonymize v0.1.0 — regex-based PII redaction

First release. Pure-Rust, in-WASM, regex-only, declares no
permissions. Suitable as a first redaction pass after
text.extract before any cloud-LLM step.

Detection categories:

  EMAIL          RFC-5321-ish local@domain, IDN-aware.
  PHONE          International (+CC …) and DE national
                 (030 …, 0151-…) shapes, 7..20 raw digits.
  IBAN           Word-bounded [A-Z]{2}\d{2}[A-Z0-9]{11,30}.
                 Structural only — MOD-97 checksum
                 deliberately skipped so partial / truncated
                 tokens in running text still get redacted.
  BIC            8 or 11 uppercase alnum.
  IPV4           Four 0..255 octets, dot-separated.
  GERMAN_TAX_ID  11 consecutive digits, word-bounded.
  CUSTOM         Operator-supplied bare terms from the
                 newline-separated `custom_terms` input,
                 matched whole-word case-insensitive.

Token shape: ⟦TYPE_N⟧ — U+27E6 / U+27E7 mathematical white
square brackets. Distinct from any plain ASCII `[…]` already
present in source text (Markdown links, legal citations,
code blocks) so a reviewer never has to guess which `[…]`
is a redaction.

Outputs:

  anonymized  text  Input with PII replaced by ⟦TYPE_N⟧.
                    Counter restarts at 1 per type so the
                    tokens stay operator-readable.
  report      json  { redactions: [{type, token, original,
                    offset}…], counts: { TYPE: n, … } }.
                    Full original-text reconstruction is
                    possible from this — the GDPR
                    Art. 32(1)(a) "ability to undo"
                    requirement.

Quality bar (7 unit tests):
  * email round-trip
  * IBAN + BIC don't eat each other
  * three phone-number shapes redact
  * IPv4 only matches valid 0..255 octets
  * custom_terms case-insensitive
  * no double-redaction on overlapping patterns
  * per-category counter resets correctly

Built artefact: target/wasm32-wasip2/release/text_anonymize.wasm
(~180 KiB stripped).

NER for free-text names / organisations / locations is the
v0.2.0 plan once a benchmarked ONNX model is selected; the
operator's `custom_terms` field is the v0.1.0 escape hatch.

Signed-off-by: flemming-it <sf@flemming.it>

Cargo.toml

@@ -0,0 +1,37 @@
+# Standalone Cargo.toml — targets wasm32-wasip2.
+#
+# Build with:
+#   cargo build --release --target wasm32-wasip2
+
+[package]
+name = "text_anonymize"
+version = "0.1.0"
+edition = "2024"
+authors = ["Dr. Stefan Flemming <platform@flemming.ai>"]
+license = "Apache-2.0"
+publish = false
+description = "F∆I module — regex-based PII anonymization for plain text"
+repository = "https://git.flemming.ai/fai-modules/text-anonymize"
+rust-version = "1.85"
+
+[lib]
+crate-type = ["cdylib", "rlib"]
+
+[dependencies]
+fai-module-sdk = { git = "https://git.flemming.ai/fai/module-sdk.git", branch = "main" }
+serde = { version = "1", features = ["derive"] }
+serde_json = "1"
+# Regex without the unicode-perl / unicode-script / unicode-segment
+# features keeps the wasm payload <300kB. The patterns this module
+# uses (email, phone, IBAN, BIC, IPv4, German tax id, name list)
+# are ASCII-class enough to live without the full Unicode tables.
+regex = { version = "1.10", default-features = false, features = ["std", "unicode-case", "unicode-perl"] }
+
+[dev-dependencies]
+serde_json = "1"
+
+[profile.release]
+opt-level = "s"
+lto = true
+codegen-units = 1
+strip = true