Giving autonomous AI systems the capacity to write code, call shell tools, and execute scripts inside an engineering environment creates massive new security attack vectors. From indirect prompt injections hidden in untrusted git branches to excessive tool execution permissions, a misconfigured agent can quickly become a malicious pipeline threat.
This security architecture talk maps out a complete Zero-Trust defensive framework for running agentic systems in enterprise environments. Using our multi-agent software factory as a live model, we dissect how to build secure, isolated execution sandboxes for Model Context Protocol (MCP) tools. We explore how to manage non-human operational identities, implement strict API traffic gating, and construct automated verification layers that intercept and quarantine unauthorized agent actions before they compromise infrastructure.
What you will learn:

- Threat Vector Analysis: Identifying security vulnerabilities unique to autonomous systems, including prompt injection and privilege escalation.
- Sandboxed Execution: Implementing isolated runtime perimeters around automated tools to minimize agent blast radiuses.
- Identity Gating: Best practices for authenticating and logging agentic machine-to-machine communications across corporate networks.