AI agents call scan_linear to retrieve information from N0s1 without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Although secret scanning touches sensitive information, the tool itself only retrieves and analyzes data from Linear without modifying, executing operations, deleting, or moving money. The severity is low because the tool performs passive inspection rather than active exploitation—it reads existing data to identify potential leaks.
From the tool's definition Tool description explicitly states 'Read Linear issues and comments' with the purpose of detection (scanning for secrets), not modification or deletion.
Attacks that exploit this kind of access
Read Linear issues and comments to detect leaked secrets (API keys, tokens, passwords). It is categorised as a Read tool in the N0s1 MCP Server, which means it retrieves data without modifying state.
Register the N0s1 MCP server in PolicyLayer and add a rule for scan_linear: 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 N0s1. Nothing to install.
scan_linear is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the scan_linear 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_linear. 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_linear is provided by the N0s1 MCP server (spark1security/n0s1-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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