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OpenAI Misaligned Models: From Reports to Tests
OpenAI misaligned models made headlines, but what should you actually test? See how to turn the disclosed cases into tests you can run and prove.
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LLM Penetration Testing Checklist: Proof Over Output
An LLM penetration testing checklist built around evidence: what to map, what to attack, and how to prove impact. See the checks in full.
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AI Coding Agent Security: 7 Attack Paths to Test
AI coding agent security tested properly: seven attack paths from prompt injection to shell abuse, how to prove each one, and the controls that hold. Read on.
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AI Red Teaming Methodology: From Scope to Proof
A working AI red teaming methodology: map permissions first, test five attack classes in order, and prove consequence. See how to structure it.
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MCP Server Prompt Injection: Proving the Blast Radius
MCP server prompt injection is easy to demo and hard to prove. See how to test to consequence, scope tokens and write findings that hold up.
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How to Red Team an LLM: A 5-Phase Field Guide
How to red team an LLM in five phases, from mapping tool permissions to proving consequence and writing findings that survive retest. See the method.
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Automated LLM Red Teaming: What It Misses
Automated LLM red teaming finds jailbreaks at scale but misses tool abuse and excessive agency. See where to automate and what still needs a human.
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MCP Server Penetration Testing: A Tester’s Checklist
MCP server penetration testing, step by step: map the tool surface, test tool poisoning and tool abuse, prove real impact. See the full checklist.
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AI Penetration Testing: How to Scope It Properly
AI penetration testing covers two different jobs. See how to scope each one, what to ask a provider, and how to judge findings you can act on.
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AI-Assisted Pentest Tools: What Works and What Is Hype
The tools that work let the model organise findings that real measurement produced. Ask any tool where its facts come from.