从视频文件中提取音频
AI agents use extract_audio_from_video to create or update resources in FFmpeg Python MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your FFmpeg Python MCP Server environment.
This tool reads a video file and writes a new audio file extracted from it. It creates a new output file without modifying or destroying the source, making it a Write operation. Misuse could overwrite existing audio files, hence medium severity.
From the tool's definition 从视频文件中提取音频 (Extract audio from video file)
Attacks that exploit this kind of access
从视频文件中提取音频. It is categorised as a Write tool in the FFmpeg Python MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the FFmpeg Python MCP Server MCP server in PolicyLayer and add a rule for extract_audio_from_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 FFmpeg Python MCP Server. Nothing to install.
extract_audio_from_video is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the extract_audio_from_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.
Set action: deny in the PolicyLayer policy for extract_audio_from_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.
extract_audio_from_video is provided by the FFmpeg Python MCP Server MCP server (mabh111111/ffmpeg_python_mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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