Low Risk

blockrun_video

Generate short AI videos via BlockRun x402 (async, client-polled). Turns a text prompt (and optional seed image) into a short MP4 clip. The tool submits the job, then polls until the video is ready (typical total wall-time 60-180s; 5 min hard cap). Payment is settled only when upstream returns a ...

Part of the Blockrun server.

blockrun_video is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call blockrun_video to retrieve information from Blockrun without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though blockrun_video only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "blockrun_video": {}
  }
}

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These attack patterns abuse exactly the kind of access blockrun_video gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so blockrun_video only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the blockrun_video tool do? +

Generate short AI videos via BlockRun x402 (async, client-polled). Turns a text prompt (and optional seed image) into a short MP4 clip. The tool submits the job, then polls until the video is ready (typical total wall-time 60-180s; 5 min hard cap). Payment is settled only when upstream returns a finished video \u2014 if the job fails or we give up, you are not charged. Models (Seedance defaults bumped to 720p + synced audio on the gateway): - azure/sora-2 ($0.10/sec, 720p + synced audio, text-to-video) \u2014 OpenAI Sora 2 via Azure AI Foundry. duration_seconds must be 4, 8, or 12 (4s default -> ~$0.42/clip). No image_url / RealFace. - xai/grok-imagine-video ($0.05/sec, 8s default -> $0.42/clip) \u2014 stylized, fast - bytedance/seedance-1.5-pro (~$0.092/sec, 720p + audio t2v, 5s default up to 10s) \u2014 cheapest Seedance, token-priced upstream - bytedance/seedance-2.0-fast (~$0.238/sec text \xB7 ~$0.140/sec image-to-video, 720p + audio, ~60-80s gen) \u2014 sweet-spot price/quality; supports BytePlus RealFace assets - bytedance/seedance-2.0 (~$0.298/sec text \xB7 ~$0.183/sec image-to-video, 720p + audio Pro) \u2014 highest quality; supports BytePlus RealFace assets RealFace: to generate video of a SPECIFIC real person, first enroll them with blockrun_realface (returns a ta_xxxx asset id), then pass real_face_asset_id here with a Seedance 2.0 model. Mutually exclusive with image_url. Returns a permanent blockrun-hosted MP4 URL (the gateway mirrors the asset to GCS so URLs don. It is categorised as a Read tool in the Blockrun MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on blockrun_video? +

Register the Blockrun MCP server in PolicyLayer and add a rule for blockrun_video: 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 Blockrun. Nothing to install.

What risk level is blockrun_video? +

blockrun_video is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit blockrun_video? +

Yes. Add a rate_limit block to the blockrun_video 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.

How do I block blockrun_video completely? +

Set action: deny in the PolicyLayer policy for blockrun_video. 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.

What MCP server provides blockrun_video? +

blockrun_video is provided by the Blockrun MCP server (@blockrun/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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