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author: @ivolake
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Agent Skills for Large Language Models: Architecture, Acquisition, Security, and Path Forward

As agents load “skills” (instructions/code/resources) on demand—e.g., via MCP—the trust boundary shifts from model weights to the skill acquisition/runtime layer. The practical security question is how progressive disclosure and portable skill definitions constrain untrusted skills so they can’t silently expand tool privileges or data access.

#MCP #AgentSecurity #AISecurity #Research

https://openreview.net/forum?id=Er0p92BsmW
Forwarded from AISecHub
AI Coding Agents as Attack Surface: MCP, Poisoning, and Miasma

The core risk is a trust-boundary mismatch: coding agents ingest untrusted inputs (e.g., MCP tool outputs or repo content) but can act with developer-level privileges, so poisoning and instruction smuggling can turn “context” into autonomous actions.

#MCP #AgentSecurity #AISecurity #Report

https://labs.cloudsecurityalliance.org/research/ai-coding-agent-attack-surface-mcp-repository-poisoning-v1-0