[Local Lab]: Agentic Overdelegation
Demo to explore how AI agents can be manipulated to misuse tools
Demo to explore how AI agents can be manipulated to misuse tools
What would you target first in a prompt pipeline that scrapes the web?
MCP architectures create hidden pathways for LLM compromise
Understanding the Critical Divide in Responsible AI
Guardrails can steer LLMs, but they don’t stop a determined attacker
Shadow agents are stealth behaviors that emerge in multi-agent LLM systems
In agentic LLMs, memory is a persistence layer attackers can quietly poison for long-term control
Tool chaining in Agentic LLMs isn’t just a feature. It’s a hidden security collapse waiting to happen.
How shared tool access in multi-tenant MCP servers turns structured prompts into a hidden attack surface
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What happens when classic web exploits meet modern AI?
How attackers use invisible characters to bypass LLM filters and inject prompts without a trace