Insights/AI Security

AI Security

Securing AI systems: prompt injection, LLM and RAG application risks, agent security, the OWASP LLM Top 10, and shadow AI. Fixes are architectural, not prompt wording.
§ 0111 articles
01
AI Security
AI penetration testing: how to test LLM apps, agents, and RAG
AI penetration testing covers an attack surface a standard pentest was never built for. See what it tests, how it works, and how it differs from red teaming.
June 13, 2026
8 min read
02
AI Security
AI red teaming: a practical guide for security teams
AI red teaming simulates a determined adversary against your models, agents, and guardrails. See how it differs from a pentest and how to run it well.
June 13, 2026
7 min read
03
AI Security
Securing AI agents: the new attack surface of agentic AI
When AI can take actions, a manipulated model becomes a manipulated actor. See why agentic AI is a new attack surface and how to secure your agents.
June 13, 2026
6 min read
04
AI Security
MCP security: risks of the Model Context Protocol and how to manage them
The Model Context Protocol connects AI models to tools and data, and that link is a new attack surface. See the risks it adds and how to secure it.
June 14, 2026
5 min read
05
AI Security
RAG security: protecting retrieval-augmented generation systems
Retrieval-augmented generation gives models access to your data, and that data joins the attack surface. See how RAG gets attacked and how to secure it.
June 14, 2026
11 min read
06
AI Security
AI data and model poisoning: how it works and how to defend against it
Data poisoning corrupts what an AI system learns or retrieves, so it fails in ways the attacker chooses. See how these attacks work and how to defend.
June 14, 2026
10 min read
07
AI Security
LLM jailbreaks explained: how they work and how to defend
A jailbreak makes a model do what its safety controls were meant to prevent. See how LLM jailbreaks work, how they differ from injection, and the defenses.
June 14, 2026
11 min read
08
AI Security
The OWASP Top 10 for LLM Applications, explained
The OWASP Top 10 for LLM Applications is the reference list of the most critical AI application risks. See what each of the ten risks means and how to fix it.
June 14, 2026
10 min read
09
AI Security
Deepfake fraud: AI-generated voice and video attacks on business
Deepfake fraud uses AI-generated voice and video to impersonate executives and authorize payments. See how the attacks work and how to defend your business.
June 14, 2026
10 min read
10
AI Security
AI security: how to secure LLM applications
LLM apps add an attack surface that behaves like nothing before it, and better prompts will not save you. The controls that work live in the architecture.
May 24, 2026
14 min read
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AI Security
Prompt injection is not a prompt problem
Teams keep trying to patch prompt injection with better system prompts. The real fix lives in the architecture, not the wording. Here is what stops it.
May 28, 2026
14 min read