Best AI Security Articles: A Curated Reading List

There is no shortage of writing about AI security; there is a serious shortage of writing worth reading more than once. This curated list of the best ai security articles is intentionally short. Each entry is something practitioners on this team have actually used to make a better decision, write a better defense, or explain a real risk to a stakeholder. The list is grouped by what the article is for, not by who published it.

Foundational Reading — Read These First

Article	Why It Matters	Type
OWASP Top 10 for LLM Applications ↗	The vocabulary every AI security conversation now uses	Reference
Greshake et al., Indirect Prompt Injection (arXiv 2302.12173) ↗	The paper that named and demonstrated the most important attack class	Research paper
Simon Willison’s prompt injection archive ↗	The single best ongoing chronicle of attack techniques in plain English	Blog series
NIST AI 600-1: Generative AI Profile ↗	The control framework U.S. enterprise procurement is converging on	Government guidance

If you read nothing else, read these four. The Greshake paper alone reframes how to think about every input an LLM ever sees. Simon Willison’s archive is the closest thing to a real-time threat intel feed for attack techniques.

On Prompt Injection — Attack Side

Article	What It Adds
Anthropic — Many-shot jailbreaking ↗	Shows how long context windows enable a new class of attack
Lakera — Prompt injection attacks handbook	Practical taxonomy of injection patterns seen in production
OpenAI — Disrupting deceptive uses of AI ↗	Lessons from real-world abuse on a major API
Kai Greshake’s blog — Inside the world of indirect prompt injection	Long-form follow-up to the original paper, with new attack chains

For a curated, frequently-updated database of jailbreak prompts and techniques, jailbreakdb.com ↗ and the technical writeups at aisec.blog ↗ cover the offensive side in operational detail.

On Defense and Guardrails

Article	What It Adds
Lilian Weng — Adversarial Attacks on LLMs ↗	Comprehensive technical survey of attack classes and known defenses
Anthropic — Constitutional AI ↗	The theoretical basis behind a major class of safety training
Microsoft — PyRIT release post ↗	Practical view from one of the largest production red-team programs
Google DeepMind — Frontier Safety Framework ↗	Capability-thresholds approach to model deployment risk

The Lilian Weng survey is the most technically dense single reference for engineers building defenses. Defensive technique writeups also live at guardml.io ↗.

On Red Teaming

Article	What It Adds
Microsoft — Lessons from red-teaming 100 generative AI products ↗	Patterns from a substantial corpus of real engagements
Anthropic — Frontier red team blog series	Inside view of how a frontier lab structures pre-deployment testing
OWASP — AI Red Teaming Guide ↗	Checklist-format guide aimed at organizations standing up the function
MITRE ATLAS — Case study series	Documented real-world AI attack scenarios mapped to ATT&CK-style techniques

For tooling comparisons see our AI red teaming tools guide.

On Agent Security

The agent security literature is still young, but a few pieces are already canonical:

• Computer use safety considerations ↗ — Anthropic’s threat model for desktop-driving agents
• Prompt injection in MCP tool ecosystems — community writeups (see Simon Willison’s archive) that surface the new injection surface introduced by tool servers
• Securing AI Agents — OWASP draft ↗ — early-stage but the direction is being set

Our own coverage of agent security tooling maps the defenses to these threats.

On Incidents and Real-World Failures

Article	What It Adds
Stanford CRFM — Foundation model transparency reports	Structured evaluation of what major model vendors disclose
AI Incident Database — Yearly summary reports	Longitudinal view of public AI failures and harms
ai-alert.org — Network feed	Curated AI incident, CVE, and disclosure tracking
ENISA — AI threat landscape reports	Annual European-perspective threat assessments

Reviewing actual incidents is the fastest way to calibrate intuition about what risks are real versus theoretical. Independent tool reviews live at aisecreviews.com ↗.

On Governance and Policy

• EU AI Act explanatory guidance ↗ — keep one bookmark for the canonical text and one for high-quality plain-language explainers
• NIST AI 100-2: Adversarial Machine Learning Taxonomy — the formal vocabulary for adversarial ML, increasingly referenced in regulation
• Cloud Security Alliance — AI Security Working Group outputs ↗ — vendor-neutral practitioner guidance

Policy commentary on the neuralwatch.org ↗ site tracks ongoing regulatory developments.

What Got Cut

Articles that don’t make this list: vendor blog posts that read as marketing without measurement, “Top 100” listicles, anything reliant on screenshots of jailbreak prompts in chat UIs without an underlying technique to teach. The bar for inclusion is that an experienced practitioner can read the piece and walk away with a different decision they’d make next week.

Update Cadence

This list is reviewed quarterly. Foundational entries are stable; the agent-security, MCP injection, and incident sections see the most churn quarter-to-quarter. New entries replace older ones rather than accumulate — the value of the list is its size.

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Sources

• OWASP Top 10 for Large Language Model Applications ↗ — The taxonomy referenced throughout this curation.
• Greshake et al. — Indirect Prompt Injection (arXiv 2302.12173) ↗ — The foundational paper on indirect injection attacks.
• Anthropic — Many-shot jailbreaking research ↗ — Representative example of frontier-lab attack research worth tracking.
• Simon Willison — Prompt injection writing archive ↗ — The most useful single ongoing source on prompt injection in plain English.