AI agents invoke run-rerun to trigger actions in Python. 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 triggers re-execution of existing workflow runs, which initiates external operations and processes whose effects depend on the workflow configuration and arguments (run ID, job selection). While the tool references workflow orchestration rather than arbitrary code execution, it fundamentally executes pre-defined but potentially impactful automation pipelines.
From the tool's definition Re-runs a workflow run by ID. Optionally re-runs only failed jobs or a specific job.
Attacks that exploit this kind of access
Re-runs a workflow run by ID. Optionally re-runs only failed jobs or a specific job. Returns structured result with run ID, status, and URL. It is categorised as a Execute tool in the Python MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Python MCP server in PolicyLayer and add a rule for run-rerun: 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 Python. Nothing to install.
run-rerun 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 run-rerun 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 run-rerun. 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.
run-rerun is provided by the Python MCP server (Dave-London/Pare). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
run-rerun is one line of Python's registry record.
The record carries the whole server: verified identity, auth posture, risk grade, every tool classified, recommended policy — re-checked continuously.
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