AI agents use updateFilter to create or update resources in MCP Atlassian Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your MCP Atlassian Server environment.
The tool modifies existing Jira filter configurations, which are data assets but not core operational records (issues, projects). The change is reversible and has limited blast radius compared to Execute or Destructive categories. An AI agent misusing this tool could alter shared filters affecting multiple users' workflows, but without permanent data loss or financial impact.
From the tool's definition Tool name 'updateFilter' and description 'Update an existing filter in Jira' indicate modification of existing data (filters are saved searches/configurations in Jira). This is a reversible change—filters can be modified again or deleted.
Documented attack patterns abuse exactly the kind of access updateFilter gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and MCP Atlassian Server, and nothing reaches the server without passing your rules. This is the rule we recommend for updateFilter:
{
"version": "1",
"default": "deny",
"tools": {
"updateFilter": {
"limits": [
{
"counter": "updatefilter_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
} updateFilter stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Update an existing filter in Jira. It is categorised as a Write tool in the MCP Atlassian Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the MCP Atlassian Server MCP server in PolicyLayer and add a rule for updateFilter: 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 MCP Atlassian Server. Nothing to install.
updateFilter 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 updateFilter 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 updateFilter. 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.
updateFilter is provided by the MCP Atlassian Server MCP server (phuc-nt/mcp-atlassian-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 24 MCP Atlassian Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
24 MCP Atlassian Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.