Open Source Container Scanners Worth Running on Sandbox Base Images
Layer image, permission, and runtime scanners, since none alone covers agent risk.
Section
18 stories in Features.
Layer image, permission, and runtime scanners, since none alone covers agent risk.
Vendors preserve files, live processes, or forks, and the differences decide what your agent keeps.
A model-and-sandbox pairing guide built on tool use, output discipline, and context.
Time-slicing, MPS, and MIG each sacrifice one property to optimize two others.
Snapshot restore and pre-warming reveal which sub-100ms claims hold up.
Isolated execution environments weren't built for agents that reason across steps.
Choosing between Docker compatibility and multi-tenant security requires checking both.
Containers, microVMs, and runtimes each balance isolation strength against startup cost.
The isolation mechanism you choose sets both your security boundary and performance ceiling.
MCP is a standardized protocol connecting AI systems to external tools and data.
MCP servers are real programs, and a sandbox limits the damage.
Shared-kernel containers fail untrusted AI code, and microVMs now fix it.
Shared kernels fail untrusted AI code, and Docker now agrees.
Five criteria for choosing a sandbox that safely runs AI-written code.
Northflank, GKE Agent Sandbox, and AgentCore compared on BYOC.
Agent frameworks trust model output too much, and sandboxes must assume it.
Connect Python functions to AI agents using FastMCP's decorator-based tool registration.
Why C code in AI sandboxes needs hardware isolation, not just containers.