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).
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'
Attacks that exploit this kind of access
The rule that runs webgpu_timing_analysis safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Jshookmcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For webgpu_timing_analysis, this is the rule to start with:
webgpu_timing_analysis stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Jshookmcp, apply this rule, and every webgpu_timing_analysis call is checked against it from then on.
Questions about 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). 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.
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.
webgpu_timing_analysis 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 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.
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.
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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