Low Risk

hash_info

Get algorithm info

Part of the Pypi:mcp Hashlib server.

hash_info is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

SECURE PYPI:MCP HASHLIB →

Free to start. No card required.

AI agents call hash_info to retrieve information from Pypi:mcp Hashlib 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 hash_info 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.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "hash_info": {}
  }
}

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.

ENFORCE ON MY PYPI:MCP HASHLIB →

View all 22 tools →

These attack patterns abuse exactly the kind of access hash_info 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_info only ever does what you allow.

SECURE PYPI:MCP HASHLIB →

Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the hash_info tool do? +

Get algorithm info. It is categorised as a Read tool in the Pypi:mcp Hashlib MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on hash_info? +

Register the Pypi:mcp Hashlib MCP server in PolicyLayer and add a rule for hash_info: 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_info? +

hash_info is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit hash_info? +

Yes. Add a rate_limit block to the hash_info 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_info completely? +

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

hash_info 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.

Free to start. No card required.

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

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.