Low Risk

measure_from_photo

「写真を撮ったので寸法を測りたい」「この隙間に合う棚を探したい」のときに呼ぶ。 ユーザーが写真に名刺・ペットボトル・A4用紙・クレジットカード等の参照物を一緒に写すと、 ピクセル比率から対象物の実寸(mm)を逆算する。 【AIの役割】写真をVisionで解析し、参照物と対象物それぞれのピクセル幅・高さを読み取ってこのツールに渡す。 対応参照物: 名刺(91×55mm)、クレジットカード(85.6×54mm)、ペットボトル500ml(65×205mm)、A4用紙(210×297mm)、500円玉(∅26.5mm)、1円玉(∅20mm)、スマホ(71.5×147mm)、ティッシュ箱(240×...

Risk signalsHigh parameter count (15 properties)

Part of the AI Furniture & Home Product Hub server.

measure_from_photo 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 measure_from_photo to retrieve information from AI Furniture & Home Product Hub 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 measure_from_photo 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": {
    "measure_from_photo": {}
  }
}

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

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so measure_from_photo 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 measure_from_photo tool do? +

「写真を撮ったので寸法を測りたい」「この隙間に合う棚を探したい」のときに呼ぶ。 ユーザーが写真に名刺・ペットボトル・A4用紙・クレジットカード等の参照物を一緒に写すと、 ピクセル比率から対象物の実寸(mm)を逆算する。 【AIの役割】写真をVisionで解析し、参照物と対象物それぞれのピクセル幅・高さを読み取ってこのツールに渡す。 対応参照物: 名刺(91×55mm)、クレジットカード(85.6×54mm)、ペットボトル500ml(65×205mm)、A4用紙(210×297mm)、500円玉(∅26.5mm)、1円玉(∅20mm)、スマホ(71.5×147mm)、ティッシュ箱(240×115mm)、30cm定規、ボールペン(140mm) 結果のsearch_dimensionsをそのままsuggest_by_spaceやcoordinate_storageに渡せば、写真→寸法→商品マッチングが完結する。 信頼度が低い場合は「メジャーで実測を」と伝えること。. It is categorised as a Read tool in the AI Furniture & Home Product Hub MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on measure_from_photo? +

Register the AI Furniture & Home Product Hub MCP server in PolicyLayer and add a rule for measure_from_photo: 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 AI Furniture & Home Product Hub. Nothing to install.

What risk level is measure_from_photo? +

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

Can I rate-limit measure_from_photo? +

Yes. Add a rate_limit block to the measure_from_photo 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 measure_from_photo completely? +

Set action: deny in the PolicyLayer policy for measure_from_photo. 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 measure_from_photo? +

measure_from_photo is provided by the AI Furniture & Home Product Hub MCP server (https://ai-furniture-hub.onrender.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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