AI agents invoke kill_query to trigger actions in Postgres. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool terminates active database sessions/processes by PID. While not strictly destructive to data, it forcibly interrupts running queries and connections, which can cause transaction rollbacks, disrupt active users, and impact database availability. The 'terminate' mode (implied by 'mode=') may be more forceful than cancel.
From the tool's definition 'Cancel or terminate a backend session by PID' — kills a running database backend process
Attacks that exploit this kind of access
Cancel or terminate a backend session by PID. mode=. It is categorised as a Execute tool in the Postgres MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Postgres MCP server in PolicyLayer and add a rule for kill_query: 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 Postgres. Nothing to install.
kill_query is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the kill_query 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 kill_query. 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.
kill_query is provided by the Postgres MCP server (teja-sudo/postgres-mcp-server). 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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