testland/pii-masking-pipeline-builder
Build-an-X workflow that produces a PII masking pipeline spec from a source-data inventory. Walks the author through (1) classifying each field against pii-categories-reference, (2) picking a masking operator from data-masking-techniques-reference, (3) deciding pseudonymisation (reversible, in GDPR scope) vs anonymisation (irreversible, out of scope), (4) ordering the pipeline (detect → operator → audit), and (5) emitting a deployable config for Presidio + Faker + Synthea wrappers. Output is a YAML pipeline spec plus a per-field rationale table. Use after classifying a dataset's PII risk; this is the workflow that translates classification into runnable masking config.
75
94%
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Low
Low-risk findings worth noting
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The required workflow explicitly includes a “Free-text detect + mask” step that runs `presidio-pii-detection` on string columns (e.g., user-authored comment text in datasets), which at runtime would cause outsider-authored free-form content to be ingested/read by the LLM context for detection (indirect prompt-injection risk).
- Audited
- Security analysis