End a recorded browser session: trajectory-end with verdict, rvf compact, AIDefence pre-store gate (best-effort), and AgentDB index in the browser-sessions namespace. Use when native WebFetch is wrong because you need real browser automation — JS-heavy SPA scraping, login flows with cookie reuse,...
AI agents invoke browser_session_end to trigger actions in Ruflo. 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 a browser automation session and performs several side-effecting operations: finalizing a trajectory with a verdict, compacting session data, gating PII through AIDefence before storing, and indexing results in AgentDB. It drives real browser automation (login flows, cookie reuse, DOM interaction) and commits session artifacts to persistent storage.
From the tool's definition End a recorded browser session: trajectory-end with verdict, rvf compact, AIDefence pre-store gate (best-effort), and AgentDB index in the browser-sessions namespace
Attacks that exploit this kind of access
End a recorded browser session: trajectory-end with verdict, rvf compact, AIDefence pre-store gate (best-effort), and AgentDB index in the browser-sessions namespace. Use when native WebFetch is wrong because you need real browser automation — JS-heavy SPA scraping, login flows with cookie reuse, replay against DOM-drifted versions, AIDefence PII gating before content reaches Claude. For static HTML pages, native WebFetch is faster and free. It is categorised as a Execute tool in the Ruflo MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Ruflo MCP server in PolicyLayer and add a rule for browser_session_end: 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 Ruflo. Nothing to install.
browser_session_end 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 browser_session_end 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 browser_session_end. 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.
browser_session_end is provided by the Ruflo MCP server (ruvnet/ruflo). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
browser_session_end is one line of Ruflo'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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