augment_findings · Trailmark MCP Server MCP: Risk & Policy

WHAT IT DOES

What augment_findings does on Trailmark MCP Server

AI agents use augment_findings to create or update resources in Trailmark MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Trailmark MCP Server environment.

WHY IT NEEDS A POLICY

Why augment_findings needs a policy

The tool writes findings data into an existing graph structure, which is a reversible modification. It does not execute arbitrary code, delete data, or move money. The blast radius is medium because incorrect or malicious findings could mislead security analysis, but the operation itself is not destructive and can be undone or corrected by clearing annotations or reimporting.

From the tool's definition Tool description states 'Import findings into the current graph' — this creates or modifies data in the graph by adding findings from external sources (SARIF or weAudit formats).

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

augment_findings Rate-limited

augment_findings 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "augment_findings": {
      "limits": [
        {
          "counter": "augment_findings_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Trailmark MCP Server, so you can run agents against it safely.

FAQ

Questions about augment_findings

What does the augment_findings tool do? +

Import findings into the current graph from SARIF or weAudit. It is categorised as a Write tool in the Trailmark MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on augment_findings? +

Register the Trailmark MCP Server MCP server in PolicyLayer and add a rule for augment_findings: 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 Trailmark MCP Server. Nothing to install.

What risk level is augment_findings? +

augment_findings is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit augment_findings? +

Yes. Add a rate_limit block to the augment_findings 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.

How do I block augment_findings completely? +

Set action: deny in the PolicyLayer policy for augment_findings. 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.

What MCP server provides augment_findings? +

augment_findings is provided by the Trailmark MCP Server MCP server (parsiya/trailmark-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.