filter_and_save · Tshark MCP: Risk & Policy

WHAT IT DOES

What filter_and_save does on Tshark

AI agents use filter_and_save to create or update resources in Tshark — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Tshark environment.

WHY IT NEEDS A POLICY

Why filter_and_save needs a policy

Without an explicit description, classification relies on the tool name and context. 'filter_and_save' most likely creates or modifies saved files/data (Write category) rather than irreversibly deleting (Destructive) or executing arbitrary code (Execute). In the context of a packet analysis tool, it would filter captured traffic and save the results, which is reversible.

From the tool's definition Tool name 'filter_and_save' combined with sibling tools like 'analyze_pcap_file', 'export_objects', 'export_to_json' suggests this tool filters network packet data and writes/saves results to storage. The '_save' suffix indicates data persistence.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

filter_and_save Rate-limited

filter_and_save stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "filter_and_save": {
      "limits": [
        {
          "counter": "filter_and_save_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Tshark, so you can run agents against it safely.

FAQ

Questions about filter_and_save

What does the filter_and_save tool do? +

filter_and_save. It is categorised as a Write tool in the Tshark MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on filter_and_save? +

Register the Tshark MCP server in PolicyLayer and add a rule for filter_and_save: 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 Tshark. Nothing to install.

What risk level is filter_and_save? +

filter_and_save is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit filter_and_save? +

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

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

filter_and_save is provided by the Tshark MCP server (ouonet/tshark-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.