Medium Risk

save_job

Save a job to your application tracker. Requires authentication.

Risk signalsHigh parameter count (10 properties)

Part of the Himalayas Remote Jobs server.

save_job can modify Himalayas Remote Jobs data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use save_job to create or modify resources in Himalayas Remote Jobs. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call save_job repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Himalayas Remote Jobs.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "save_job": {
      "limits": [
        {
          "counter": "save_job_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Himalayas Remote Jobs policy for all 41 tools.

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

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

What does the save_job tool do? +

Save a job to your application tracker. Requires authentication.. It is categorised as a Write tool in the Himalayas Remote Jobs MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on save_job? +

Register the Himalayas Remote Jobs MCP server in PolicyLayer and add a rule for save_job: 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 Himalayas Remote Jobs. Nothing to install.

What risk level is save_job? +

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

Can I rate-limit save_job? +

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

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

save_job is provided by the Himalayas Remote Jobs MCP server (https://mcp.himalayas.app/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Himalayas Remote Jobs tool call.

Deterministic rules across all 41 Himalayas Remote Jobs tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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