finch_build_container_image
AI agents invoke finch_build_container_image to trigger actions in AWS Labs Aurora DSQL MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
Building container images executes code and triggers external Docker/container runtime operations whose effects depend on the image contents and build arguments. This is Execute-level risk: it runs external processes and could be exploited to execute arbitrary code within the build context.
From the tool's definition Tool name 'finch_build_container_image' indicates building/compiling container images, which involves executing code and external operations. The description is empty, limiting specificity.
Documented attack patterns abuse exactly the kind of access finch_build_container_image gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and AWS Labs Aurora DSQL MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for finch_build_container_image:
{
"version": "1",
"default": "deny",
"tools": {
"finch_build_container_image": {
"limits": [
{
"counter": "finch_build_container_image_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} finch_build_container_image stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
Free to start. No card required.
finch_build_container_image. It is categorised as a Execute tool in the AWS Labs Aurora DSQL MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the AWS Labs Aurora DSQL MCP Server MCP server in PolicyLayer and add a rule for finch_build_container_image: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches AWS Labs Aurora DSQL MCP Server. Nothing to install.
finch_build_container_image is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the finch_build_container_image rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for finch_build_container_image. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
finch_build_container_image is provided by the AWS Labs Aurora DSQL MCP Server MCP server (awslabs.aurora-dsql-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from AWS Labs Aurora DSQL MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
805 AWS Labs Aurora DSQL MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.