What it means
Automation input validation verifies type, format, range, origin, authorization, and business rules before data can drive scripts, APIs, templates, or infrastructure changes.
Why it matters
Untrusted or malformed input can redirect targets, inject commands, corrupt configuration, or create actions outside the intended workflow.
Practical focus
- Define the system boundary, accountable owner, approved purpose, material risks, and decision authority for Automation Input Validation
- Use allowlists, schemas, canonicalization, bounds, context-aware escaping, source authentication, and explicit rejection with safe error handling.
- Collect and protect this evidence: schemas, validation code, negative tests, rejected-input logs, change reviews, fuzz results, and incident examples.
- Exercise this failure scenario as a planned test: a user-controlled hostname is concatenated into a shell command and turns a normal request into arbitrary execution.
Common mistakes
- Using the label Automation Input Validation without defining the exact systems, data, people, decisions, and time period in scope
- Treating a policy statement or tool demonstration as proof that Automation Input Validation operates consistently in production
- Failing to retain schemas, validation code, negative tests, rejected-input logs, change reviews, fuzz results, and incident examples in a form that lets an independent reviewer reconstruct decisions and changes
- Testing only the normal path and never rehearsing what happens when a user-controlled hostname is concatenated into a shell command and turns a normal request into arbitrary execution.
Certification relevance
This subject appears in or supports the following certification bodies of knowledge: