Update multiple work items in batch
Risk signalsBulk modifies project tracking data
Part of the Azure DevOps server.
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AI agents use mcp_ado_wit_update_work_items_batch to create or modify resources in Azure DevOps. 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 mcp_ado_wit_update_work_items_batch 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 Azure DevOps.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"mcp_ado_wit_update_work_items_batch": {
"limits": [
{
"counter": "mcp_ado_wit_update_work_items_batch_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Azure DevOps policy for all 84 tools.
These attack patterns abuse exactly the kind of access mcp_ado_wit_update_work_items_batch gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Update multiple work items in batch. It is categorised as a Write tool in the Azure DevOps MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Azure DevOps MCP server in PolicyLayer and add a rule for mcp_ado_wit_update_work_items_batch: 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 Azure DevOps. Nothing to install.
mcp_ado_wit_update_work_items_batch is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the mcp_ado_wit_update_work_items_batch 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 mcp_ado_wit_update_work_items_batch. 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.
mcp_ado_wit_update_work_items_batch is provided by the Azure DevOps MCP server (@@azure-devops/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 84 Azure DevOps tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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