# SPM-001: Classify previously unseen AI applications on first encounter


- Area: AI Security Posture Management

- Verification: Live test
- OWASP adoption tier: AT0–AT4
- Formerly: DIS-014
- URL: /r/SPM-001

**Acceptance criteria:** Identify and risk-score an AI application the platform has not seen before, without waiting for a signature, category list or catalog update, and show the evidence behind the classification.

**Why it matters:** Waiting for a catalog update leaves every new tool ungoverned during the period it is most likely to be tried.

**How to verify:** An AI tool the vendor has not seen before is classified and risk-scored on first use, with the evidence shown.

**OWASP adoption context:** Shadow AI is the primary first-encounter discovery scenario; an unfamiliar application should not require a prior catalog entry to become visible.

**Mappings:**
- NIST CSF 2.0: ID.AM-02, ID.RA-05; ISO 27001: Cl. 6.1.2, A.5.9 — Evidence-based first-encounter classification supplies timely software-inventory and risk-assessment inputs without catalog delay. A classification or score is not a maintained, owned inventory or a complete risk assessment.
- NIST AI RMF: MAP 4.1 — Evidence behind unfamiliar-app classification helps map third-party AI component risks. The buyer must validate that evidence; signature-free detection is an implementation choice, not a complete risk-mapping process.
- SOC 2: CC3.2, CC9.2 — New-service classification and scoring inform risk evaluation and supplier review. The buyer must validate scoring evidence and make the subsequent due-diligence and treatment decisions.
- ISO 42001: A.4.2 — First-encounter identity and classification evidence help identify an AI resource for documentation. A one-time classification does not establish continued operational monitoring or support.