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webgpu_timing_analysis

GPU timing analysis for side-channel detection. Measures GPU command execution time variance to detect cache-based side-channel attacks (Graz University 2025 research).

SERVERJshookmcp SOURCE@jshookmcp/jshook
High RISK CLASS
Category Execute
Parameters 00 required
Recommended Rate-limitedsee the rule below
Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-vmoranv-jshookmcp/webgpu-timing-analysis.md

What webgpu_timing_analysis does on Jshookmcp

AI agents invoke webgpu_timing_analysis to trigger actions in Jshookmcp. 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.

Why webgpu_timing_analysis is rated High

This tool actively executes GPU commands and measures their timing variance to detect side-channel vulnerabilities. It runs real GPU workloads rather than passively reading data, placing it in Execute.

From the tool's definition 'GPU timing analysis', 'Measures GPU command execution time variance', 'detect cache-based side-channel attacks'

Questions about webgpu_timing_analysis

What does the webgpu_timing_analysis tool do? +

GPU timing analysis for side-channel detection. Measures GPU command execution time variance to detect cache-based side-channel attacks (Graz University 2025 research). It is categorised as a Execute tool in the Jshookmcp MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on webgpu_timing_analysis? +

Register the Jshook MCP server in PolicyLayer and add a rule for webgpu_timing_analysis: 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 Jshookmcp. Nothing to install.

What risk level is webgpu_timing_analysis? +

webgpu_timing_analysis is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit webgpu_timing_analysis? +

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

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

webgpu_timing_analysis is provided by the Jshook MCP server (@jshookmcp/jshook). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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