Generate a zero-pipeline-minutes deploy bundle: stack-aware Dockerfile, .dockerignore, dev compose, render.yaml (Render existing-image), wrangler.pages.toml + wrangler.containers.toml + worker.ts (Cloudflare), bash/PowerShell push scripts, and a qualification report. The project builds locally in...
AI agents invoke deploy to trigger actions in AXIS iliad. 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.
While 'deploy' is nominally about generation, the tool orchestrates automated deployment workflows that execute against production infrastructure. The generated artifacts (push scripts, wrangler configs) trigger actual deployments whose side effects (resource creation, traffic routing, service updates) depend on the bundle contents and cannot be safely previewed without execution.
From the tool's definition Tool generates deployment bundles including Dockerfiles, compose files, push scripts, and qualification reports that trigger external operations: 'pushes images to GHCR', 'Render/Cloudflare just pulls'.
Attacks that exploit this kind of access
Generate a zero-pipeline-minutes deploy bundle: stack-aware Dockerfile, .dockerignore, dev compose, render.yaml (Render existing-image), wrangler.pages.toml + wrangler.containers.toml + worker.ts (Cloudflare), bash/PowerShell push scripts, and a qualification report. The project builds locally in VSCode, pushes images to GHCR or via wrangler, and Render/Cloudflare just pulls — no GitHub Actions minutes, no Render build pipeline minutes, no CF build minutes. It is categorised as a Execute tool in the AXIS iliad MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the AXIS iliad MCP server in PolicyLayer and add a rule for deploy: 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 AXIS iliad. Nothing to install.
deploy 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 deploy 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 deploy. 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.
deploy is provided by the AXIS iliad MCP server (lastmanupinc-hub/axis-iliad). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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