Detect anomalies in time-series data — use after pulling numeric metrics from monitoring APIs, financial data sources, IoT sensors, or spreadsheet columns. Send a single numeric array and specify a window size. Early windows define 'normal', recent windows are tested for anomalies. Typical workfl...
Part of the WaveGuard server.
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AI agents call waveguard_scan_timeseries to retrieve information from WaveGuard 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 waveguard_scan_timeseries 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.
{
"version": "1",
"default": "deny",
"tools": {
"waveguard_scan_timeseries": {}
}
}See the full WaveGuard policy for all 19 tools.
These attack patterns abuse exactly the kind of access waveguard_scan_timeseries gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Detect anomalies in time-series data — use after pulling numeric metrics from monitoring APIs, financial data sources, IoT sensors, or spreadsheet columns. Send a single numeric array and specify a window size. Early windows define 'normal', recent windows are tested for anomalies. Typical workflow: (1) Pull a column of numbers from Sheets, a Supabase time-series table, or a metrics API. (2) Pass the array here. (3) Get back which time windows are anomalous. Examples: - Revenue monitoring: Pull monthly revenue from Sheets → detect anomalous months - Stock screening: Pull 90 days of closing prices → find unusual price windows - Server health: Pull response-time metrics → identify degradation windows - Sensor QA: Pull temperature readings from IoT API → flag sensor drift. It is categorised as a Read tool in the WaveGuard MCP Server, which means it retrieves data without modifying state.
Register the WaveGuard MCP server in PolicyLayer and add a rule for waveguard_scan_timeseries: 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 WaveGuard. Nothing to install.
waveguard_scan_timeseries is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the waveguard_scan_timeseries 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 waveguard_scan_timeseries. 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.
waveguard_scan_timeseries is provided by the WaveGuard MCP server (https://gpartin--waveguard-api-fastapi-app.modal.run/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 19 WaveGuard tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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