AI agents invoke finch_push_image to trigger actions in Amazon Location Service 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.
The name suggests pushing a container image (similar to 'docker push'), which is an Execute/Write action that pushes an image to a registry. This is an external operation with side effects. However, the description is empty, lowering confidence. Given the potential blast radius of pushing unauthorized or malicious images to a registry, severity is rated high.
From the tool's definition Tool name 'finch_push_image' — no description provided
Documented attack patterns abuse exactly the kind of access finch_push_image gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Amazon Location Service MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for finch_push_image:
{
"version": "1",
"default": "deny",
"tools": {
"finch_push_image": {
"limits": [
{
"counter": "finch_push_image_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} finch_push_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.
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finch_push_image. It is categorised as a Execute tool in the Amazon Location Service MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Amazon Location Service MCP Server MCP server in PolicyLayer and add a rule for finch_push_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 Amazon Location Service MCP Server. Nothing to install.
finch_push_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_push_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_push_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_push_image is provided by the Amazon Location Service MCP Server MCP server (awslabs.aws-location-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Amazon Location Service MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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805 Amazon Location Service MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.