AI agents invoke scan_data to trigger actions in YaraFlux MCP Server. 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.
Given the server context (YARA rule-based threat analysis on files and URLs) and the tool name 'scan_data', this tool most likely executes YARA scanning operations against data, files, or URLs. Scanning involves running analysis operations/rules against targets, which constitutes an Execute-level action.
From the tool's definition Tool name 'scan_data' on a YARA threat analysis server; description is empty/uninformative
Documented attack patterns abuse exactly the kind of access scan_data gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and YaraFlux MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for scan_data:
{
"version": "1",
"default": "deny",
"tools": {
"scan_data": {
"limits": [
{
"counter": "scan_data_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}scan_data 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.
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scan_data. It is categorised as a Execute tool in the YaraFlux MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the YaraFlux MCP Server MCP server in PolicyLayer and add a rule for scan_data: 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 YaraFlux MCP Server. Nothing to install.
scan_data 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 scan_data 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 scan_data. 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.
scan_data is provided by the YaraFlux MCP Server MCP server (threatflux/yaraflux). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from YaraFlux MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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20 YaraFlux MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.