# Control index

- [DASF-1](https://mathborgess.github.io/ai-security-wiki/wiki/controls/1.md) — SSO with IdP and MFA
- [DASF-2](https://mathborgess.github.io/ai-security-wiki/wiki/controls/2.md) — Sync users and groups
- [DASF-3](https://mathborgess.github.io/ai-security-wiki/wiki/controls/3.md) — Restrict access using IP access lists
- [DASF-4](https://mathborgess.github.io/ai-security-wiki/wiki/controls/4.md) — Restrict access using private link
- [DASF-5](https://mathborgess.github.io/ai-security-wiki/wiki/controls/5.md) — Control access to data and other objects
- [DASF-6](https://mathborgess.github.io/ai-security-wiki/wiki/controls/6.md) — Classify data
- [DASF-7](https://mathborgess.github.io/ai-security-wiki/wiki/controls/7.md) — Enforce data quality checks on batch and streaming datasets
- [DASF-8](https://mathborgess.github.io/ai-security-wiki/wiki/controls/8.md) — Encrypt data at rest
- [DASF-9](https://mathborgess.github.io/ai-security-wiki/wiki/controls/9.md) — Encrypt data in transit
- [DASF-10](https://mathborgess.github.io/ai-security-wiki/wiki/controls/10.md) — Version data
- [DASF-11](https://mathborgess.github.io/ai-security-wiki/wiki/controls/11.md) — Capture and view data lineage
- [DASF-12](https://mathborgess.github.io/ai-security-wiki/wiki/controls/12.md) — Delete records from datasets
- [DASF-13](https://mathborgess.github.io/ai-security-wiki/wiki/controls/13.md) — Use near real-time data
- [DASF-14](https://mathborgess.github.io/ai-security-wiki/wiki/controls/14.md) — Audit actions performed on datasets
- [DASF-15](https://mathborgess.github.io/ai-security-wiki/wiki/controls/15.md) — Explore datasets and identify problems
- [DASF-16](https://mathborgess.github.io/ai-security-wiki/wiki/controls/16.md) — Secure model features
- [DASF-17](https://mathborgess.github.io/ai-security-wiki/wiki/controls/17.md) — Track and reproduce the training data used for ML model training
- [DASF-18](https://mathborgess.github.io/ai-security-wiki/wiki/controls/18.md) — Govern model assets
- [DASF-19](https://mathborgess.github.io/ai-security-wiki/wiki/controls/19.md) — Manage end-to-end machine learning lifecycle
- [DASF-20](https://mathborgess.github.io/ai-security-wiki/wiki/controls/20.md) — Track ML training runs
- [DASF-21](https://mathborgess.github.io/ai-security-wiki/wiki/controls/21.md) — Monitor data and AI system from a single pane of glass
- [DASF-22](https://mathborgess.github.io/ai-security-wiki/wiki/controls/22.md) — Build models with all representative, accurate and relevant data sources
- [DASF-23](https://mathborgess.github.io/ai-security-wiki/wiki/controls/23.md) — Register, version, approve, promote, deploy and monitor models
- [DASF-24](https://mathborgess.github.io/ai-security-wiki/wiki/controls/24.md) — Control access to models and model assets
- [DASF-25](https://mathborgess.github.io/ai-security-wiki/wiki/controls/25.md) — Use retrieval augmented generation (RAG) with large language models (LLMs)
- [DASF-26](https://mathborgess.github.io/ai-security-wiki/wiki/controls/26.md) — Fine-tune large language models (LLMs)
- [DASF-27](https://mathborgess.github.io/ai-security-wiki/wiki/controls/27.md) — Pretrain a large language model (LLM)
- [DASF-28](https://mathborgess.github.io/ai-security-wiki/wiki/controls/28.md) — Create model aliases, tags and annotations
- [DASF-29](https://mathborgess.github.io/ai-security-wiki/wiki/controls/29.md) — Build MLOps workflows
- [DASF-30](https://mathborgess.github.io/ai-security-wiki/wiki/controls/30.md) — Encrypt models
- [DASF-31](https://mathborgess.github.io/ai-security-wiki/wiki/controls/31.md) — Secure model serving endpoints
- [DASF-32](https://mathborgess.github.io/ai-security-wiki/wiki/controls/32.md) — Govern and monitor access of AI model and model serving endpoints
- [DASF-33](https://mathborgess.github.io/ai-security-wiki/wiki/controls/33.md) — Manage credentials securely
- [DASF-34](https://mathborgess.github.io/ai-security-wiki/wiki/controls/34.md) — Run models in multiple layers of isolation
- [DASF-35](https://mathborgess.github.io/ai-security-wiki/wiki/controls/35.md) — Track model performance
- [DASF-36](https://mathborgess.github.io/ai-security-wiki/wiki/controls/36.md) — Set up monitoring alerts
- [DASF-37](https://mathborgess.github.io/ai-security-wiki/wiki/controls/37.md) — Set up inference tables for monitoring and debugging models
- [DASF-38](https://mathborgess.github.io/ai-security-wiki/wiki/controls/38.md) — Platform security — penetration testing, red teaming, bug bounty and vulnerability management
- [DASF-39](https://mathborgess.github.io/ai-security-wiki/wiki/controls/39.md) — Platform security — Incident Response Team
- [DASF-40](https://mathborgess.github.io/ai-security-wiki/wiki/controls/40.md) — Platform security — internal access
- [DASF-41](https://mathborgess.github.io/ai-security-wiki/wiki/controls/41.md) — Platform security — secure SDLC
- [DASF-42](https://mathborgess.github.io/ai-security-wiki/wiki/controls/42.md) — Employ data-centric MLOps and LLMOps
- [DASF-43](https://mathborgess.github.io/ai-security-wiki/wiki/controls/43.md) — Use access control lists
- [DASF-44](https://mathborgess.github.io/ai-security-wiki/wiki/controls/44.md) — Triggering actions in response to a specific event
- [DASF-45](https://mathborgess.github.io/ai-security-wiki/wiki/controls/45.md) — Evaluate models
- [DASF-46](https://mathborgess.github.io/ai-security-wiki/wiki/controls/46.md) — Store and retrieve embeddings securely
- [DASF-47](https://mathborgess.github.io/ai-security-wiki/wiki/controls/47.md) — Compare LLM outputs on set prompts
- [DASF-48](https://mathborgess.github.io/ai-security-wiki/wiki/controls/48.md) — Use hardened Runtime for Machine Learning
- [DASF-49](https://mathborgess.github.io/ai-security-wiki/wiki/controls/49.md) — Automate LLM evaluation
- [DASF-50](https://mathborgess.github.io/ai-security-wiki/wiki/controls/50.md) — Platform compliance
- [DASF-51](https://mathborgess.github.io/ai-security-wiki/wiki/controls/51.md) — Share data and AI assets securely
- [DASF-52](https://mathborgess.github.io/ai-security-wiki/wiki/controls/52.md) — Source code control
- [DASF-53](https://mathborgess.github.io/ai-security-wiki/wiki/controls/53.md) — Third-party library control
- [DASF-54](https://mathborgess.github.io/ai-security-wiki/wiki/controls/54.md) — Implement AI guardrails
- [DASF-55](https://mathborgess.github.io/ai-security-wiki/wiki/controls/55.md) — Monitor audit logs
- [DASF-56](https://mathborgess.github.io/ai-security-wiki/wiki/controls/56.md) — Restrict outbound connections from models
- [DASF-57](https://mathborgess.github.io/ai-security-wiki/wiki/controls/57.md) — Use attribute-based access controls (ABAC)
- [DASF-58](https://mathborgess.github.io/ai-security-wiki/wiki/controls/58.md) — Protect data with filters and masking
- [DASF-59](https://mathborgess.github.io/ai-security-wiki/wiki/controls/59.md) — Use clean rooms
- [DASF-60](https://mathborgess.github.io/ai-security-wiki/wiki/controls/60.md) — Rate limit number of inference queries
- [DASF-61](https://mathborgess.github.io/ai-security-wiki/wiki/controls/61.md) — Train users on AI risk taxonomy and AI/ML security
- [DASF-62](https://mathborgess.github.io/ai-security-wiki/wiki/controls/62.md) — Implement network segmentation
- [DASF-63](https://mathborgess.github.io/ai-security-wiki/wiki/controls/63.md) — Update software
- [DASF-64](https://mathborgess.github.io/ai-security-wiki/wiki/controls/64.md) — Limit access from AI models and agents
- [DASF-65](https://mathborgess.github.io/ai-security-wiki/wiki/controls/65.md) — Implement end-to-end AI traceability
- [DASF-66](https://mathborgess.github.io/ai-security-wiki/wiki/controls/66.md) — Use Human-in-the-loop feedback
- [DASF-67](https://mathborgess.github.io/ai-security-wiki/wiki/controls/67.md) — Federate authentication
- [DASF-68](https://mathborgess.github.io/ai-security-wiki/wiki/controls/68.md) — Use Securely Hosted Managed MCP Servers
- [DASF-69](https://mathborgess.github.io/ai-security-wiki/wiki/controls/69.md) — Securely host Custom MCP Servers
- [DASF-70](https://mathborgess.github.io/ai-security-wiki/wiki/controls/70.md) — Securely connect to External MCP Servers
- [DASF-71](https://mathborgess.github.io/ai-security-wiki/wiki/controls/71.md) — Log and register AI agents
- [DASF-72](https://mathborgess.github.io/ai-security-wiki/wiki/controls/72.md) — Securely store and reuse agent state
- [DASF-73](https://mathborgess.github.io/ai-security-wiki/wiki/controls/73.md) — Register prompts