# Runbook - 06 RAG Vector Classified Docs

## Objective

Show that a RAG agent retrieves only authorized chunks/documents before sending context to the LLM.

## Security Value

- Reduces over-retrieval in RAG.
- Prevents confidential chunks from being sent to the model.
- Combines vector search with data grants by classification.

## Prerequisites

- Oracle AI Database with support for `VECTOR`, `TO_VECTOR`, and `VECTOR_DISTANCE`.
- Database compatible with Oracle Deep Data Security.
- SQLcl or SQL*Plus.

## Before - Vulnerable Environment

1. From the repository root, connect as `ADMIN`:

   ```bash
   cd <repo-root>
   export TNS_ADMIN=<wallet-directory>
   sql admin@ddslab_tunnel
   ```

   Presenter note: `ADMIN` prepares the classified chunks and security personas.

   SQLcl note: after running a script with `@file.sql`, do not type `/`. The slash reruns the last command in the SQLcl buffer and can make a successful command look like an error.


Connection alias note: ddslab_tunnel is the TNS alias configured in the wallet `tnsnames.ora` for this lab. If your wallet uses another alias, replace ddslab_tunnel with your own service alias.

2. Reset the scenario:

   ```sql
   @scenarios/06-rag-vector-classified-docs/sql/99_reset.sql
   ```

   Presenter note: this removes prior Data Grants, roles, users, and test data.

3. Create chunks and personas without applying data grants:

   ```sql
   @scenarios/06-rag-vector-classified-docs/sql/00_schema.sql
   @scenarios/06-rag-vector-classified-docs/sql/01_seed_data.sql
   @scenarios/06-rag-vector-classified-docs/sql/02_identities.sql
   ```

   Presenter note: `rag_legacy_retrieval_role` simulates a broad RAG retrieval layer before DDS is enforced.

4. Show every chunk and its classification:

   ```sql
   SELECT chunk_id, document_title, department, classification, chunk_text
   FROM dds_rag_chunks
   ORDER BY chunk_id;
   ```

   Presenter note: explain that confidential chunks should not be sent to the LLM for every user.

5. Simulate the RAG question:

   ```text
   Summarize critical documents about renewals, people, and legal risks.
   ```

6. Exit and connect as Nina, a regular employee:

   ```sql
   exit
   ```

   ```bash
   sql 'nina/Welcome1_DDS!@ddslab_tunnel'
   ```

   Presenter note: Nina represents a regular employee using an internal copilot.

7. Run the vector search before DDS:

   ```sql
   @scenarios/06-rag-vector-classified-docs/sql/04_test_queries.sql
   ```

   Presenter note: before DDS, a broad retrieval path can place HR, legal, or executive confidential chunks in the LLM context.

## Expected Result Before

- The search may retrieve `HR_CONFIDENTIAL`, `LEGAL_CONFIDENTIAL`, and `EXECUTIVE_CONFIDENTIAL` chunks.
- The LLM could receive sensitive context before it even generates an answer.

## After - Applying Deep Data Security

1. Exit and reconnect as `ADMIN`:

   ```sql
   exit
   ```

   ```bash
   sql admin@ddslab_tunnel
   ```

2. Apply data grants by classification:

   ```sql
   @scenarios/06-rag-vector-classified-docs/sql/03_data_grants.sql
   ```

   Presenter note: the database now filters chunks before the LLM receives any context.

3. Test Nina after DDS:

   ```sql
   exit
   ```

   ```bash
   sql 'nina/Welcome1_DDS!@ddslab_tunnel'
   ```

   ```sql
   @scenarios/06-rag-vector-classified-docs/sql/04_test_queries.sql
   ```

   Presenter note: Nina should retrieve only `PUBLIC` and `INTERNAL` chunks.

4. Repeat the same search as HR, legal, and executive personas:

   ```bash
   sql 'heitor/Welcome1_DDS!@ddslab_tunnel'
   sql 'sofia/Welcome1_DDS!@ddslab_tunnel'
   sql 'carlos/Welcome1_DDS!@ddslab_tunnel'
   ```

   Presenter note: each persona receives only the chunk classifications authorized for that business role.

## Expected Result After

- `nina` retrieves only `PUBLIC` and `INTERNAL` chunks.
- `heitor` retrieves authorized HR content.
- `sofia` retrieves authorized legal content.
- `carlos` retrieves all chunks through the executive role.
- The RAG layer sends only authorized context to the LLM.

## Demo Evidence

- Retrieved chunk list before and after protection.
- Visible classifications by persona.
- Explanation that enforcement happens before the LLM call.

## Official References

- Oracle Deep Data Security Guide: https://docs.oracle.com/en/database/oracle/oracle-database/26/ddscg/index.html
- Create Data Grants: https://docs.oracle.com/en/database/oracle/oracle-database/26/ddscg/create-data-grants.html
- TO_VECTOR SQL Reference: https://docs.oracle.com/en/database/oracle/oracle-database/26/sqlrf/to_vector.html
- VECTOR operations in PL/SQL: https://docs.oracle.com/en/database/oracle/oracle-database/26/lnpls/sql-data-types.html