High Risk →

hash_new

Create hash with any available algorithm

Part of the Pypi:mcp Hashlib server.

hash_new can trigger actions in Pypi:mcp Hashlib, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents invoke hash_new to trigger processes or run actions in Pypi:mcp Hashlib. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.

hash_new can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.

Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "hash_new": {
      "limits": [
        {
          "counter": "hash_new_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Pypi:mcp Hashlib policy for all 22 tools.

Get this rule live on your own Pypi:mcp Hashlib server in minutes. PolicyLayer enforces it on every call, before it runs.

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View all 22 tools →

These attack patterns abuse exactly the kind of access hash_new gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so hash_new only ever does what you allow.

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Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the hash_new tool do? +

Create hash with any available algorithm. It is categorised as a Execute tool in the Pypi:mcp Hashlib MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on hash_new? +

Register the Pypi:mcp Hashlib MCP server in PolicyLayer and add a rule for hash_new: 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 Pypi:mcp Hashlib. Nothing to install.

What risk level is hash_new? +

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

Can I rate-limit hash_new? +

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

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

hash_new is provided by the Pypi:mcp Hashlib MCP server (pypi:mcp-hashlib). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Pypi:mcp Hashlib tool call.

Deterministic rules across all 22 Pypi:mcp Hashlib tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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