Highlight from The Security Paradox of Local LLMs

These attacks don’t require sophisticated exploits; they succeed by turning a developer’s normal workflow into an attack chain. It starts when a developer injects seemingly harmless content into their AI assistant’s context window.

The attack chain:

1. Attacker plants malicious prompt in likely-to-be-consumed content.
2. Developer feeds this content to their AI assistant – directly or via MCP (Model Context Protocol).
3. AI generates compromised code during normal workflow.
4. Developer deploys code or runs it locally.
5. Attacker gains persistent access or immediate control.