10. Appendix — additional resources

While working through SANS training and organizing these notes, I consulted and recommend the following materials for readers who want to go deeper. (Yi, 1/5/2026)

Entries are deduplicated; some titles appear in both industry articles and open-source repos under slightly different names. The sections below group resources by theme.

Threat modeling & design

Useful starting points include:

• Deciduous — decision tree generator for threat modeling
• Streamlit — common framework for quick ML/security engineering dashboards and prototypes

OWASP cheat sheets (GenAI / ML)

OWASP Cheat Sheet Series entries related to GenAI and ML include:

• LLM prompt injection prevention — OWASP Cheat Sheet Series
• Secure AI model ops — OWASP Cheat Sheet Series
• AI agent security — OWASP Cheat Sheet Series

Platforms, pipelines, and MLSecOps

Platform and pipeline references include:

• MLflow — open-source platform for agents, LLMs, and experiment tracking
• LLMOps tools (market guide) — AI Multiple (ML lifecycle tooling; pair with MLSecOps practices and your org’s controls)
• Awesome MLSecOps — curated list (GitHub)
• SAI #21: What is continuous training (CT) in machine learning systems? — example industry article series; substitute your preferred vendor-neutral source if needed

Model tooling, scanners, and robustness

Model security tooling references include:

• Trusted-AI Adversarial Robustness Toolbox (ART) — GitHub
• Netron — model visualization
• ModelAudit vs ModelScan: comparing ML model security scanners — Promptfoo (if URL moves, search Promptfoo + ModelAudit + ModelScan)
• 4M models scanned: Protect AI + Hugging Face — Hugging Face / Protect AI collaboration (title paraphrased; see HF blog for current post)
• Unsloth — train and run models locally (efficient fine-tuning)
• ThalesGroup / secure-ml — secure ML framework (requirements, guidelines, tools)

Agents, computer use, and memory

Agent and memory references include:

• Security of AI agents — AI Multiple (15 threat themes, OWASP-aligned framing)
• Top agentic AI design patterns for architecting AI systems — Microsoft Azure Architecture Center
• Agentic AI security: what it is and how to do it — AI Multiple (overview; diagrams live on their site)
• Computer-using agent (OpenAI) — OpenAI announcement / product page (URL may update)
• trycua / cua — open infrastructure for computer-use agents (sandboxes, SDKs)
• Memory Bank (Cline) — persistent context patterns for agentic coding assistants

RAG, vectors, and infrastructure

Retrieval and infrastructure references include:

• Powerful comparison: HNSW vs IVF indexing — Pinecone (introductory comparison; vendor-neutral alternatives exist)
• Vector DB comparison: Pinecone vs OpenSearch — example comparison article; pick your preferred vendor write-up
• Cross-service confused deputy prevention (Amazon OpenSearch) — AWS documentation

Signing, supply chain, and BOM

Supply-chain references include:

• sigstore / cosign — artifact signing and verification
• Artifact signing and verification with Sigstore Cosign — Sigstore blog (entry point for concepts)
• OWASP AIBOM Generator (Hugging Face Space)

Evaluation, RAG tradeoffs, and training modes

Evaluation and training-mode references include:

• Full fine-tuning, PEFT, prompt engineering, and RAG: which one is right for you? — representative explainer; many good posts exist
• Large Language Model Evaluation in ’26: metrics & methods — AI Multiple (broad evaluation primer; “steady the course”–style framing appears in many vendor posts)
• Security planning for LLM-based applications — Microsoft (path may change; search “LLM security planning Azure”)
• The ultimate guide to LLM security: risks & practical tips — Promptfoo docs / red teaming (example deep guide)

Concepts & culture (not single links)

Conceptual vocabulary that appears in industry discussion includes:

• PAL (program-aided language models) — start from the paper: PAL: program-aided language models (arXiv)
• “Ultrathink” in Claude Code — product/workflow terminology; see current Anthropic / Claude Code documentation.
• ANI / AGI / ASI — informal taxonomy of capability levels; treat as conceptual vocabulary, not a standard.
• Workload identity on agentic platforms — see your platform’s IAM docs (a Kagenti identity–style PDF may be vendor-specific training material).

Cybersecurity-focused small language models

Industry and research entry points include:

• Are small language models the future of cybersecurity AI? — CloudNow (example industry perspective)
• Toward cybersecurity-expert small language models — search arXiv for current papers (topic moves quickly)

Semgrep, MCP, and IDE guardrails

Static analysis and IDE workflow references include:

• Semgrep — static analysis; pairs with MCP / IDE workflows for generated code review (see Semgrep docs for MCP server details)

Jailbreaks and misuse research (examples)

Jailbreak literature moves quickly; prefer primary sources:

• “Do Anything Now” (DAN) / jailbreak families — academic and industry write-ups change frequently; search for DAN jailbreak ChatGPT or OWASP GenAI risk entries for curated context.
• Prefer primary sources (papers, OWASP, vendor security blogs) over orphaned .md filenames without a stable URL.

This appendix is a living list—prune duplicates, fix stale URLs, and add your own org’s internal standards where appropriate.