Derisk

Created By
derisk-aia year ago
AI-Native Risk Intelligence Systems, DeRisk——Your application system risk intelligent manager provides 7* 24-hour comprehensive and in-depth protection.
Overview

What is Derisk?

Derisk is an AI-native risk intelligence system designed to enhance risk analysis and management through advanced AI technologies.

How to use Derisk?

To use Derisk, developers can join the community, access the core foundational framework modules, and contribute to the development of risk intelligence applications.

Key features of Derisk?

  • AI-driven risk analysis capabilities
  • Community-driven development for collaborative enhancements
  • Modular framework for independent risk and data applications

Use cases of Derisk?

  1. Analyzing potential risks in software development projects.
  2. Enhancing decision-making processes in financial sectors.
  3. Developing intelligent agents for automated risk assessments.

FAQ from Derisk?

  • What is the main goal of the Derisk community?

The main goal is to build AI-native risk intelligence systems that provide better services and foster community collaboration.

  • How can I contribute to Derisk?

You can join our networking group on Feishu and share your experiences with other developers.

  • Is Derisk open-source?

Yes, Derisk is developed under the MIT license, making it open for contributions and modifications.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
derisk-ai
Star
6
Language
Python
License
MIT license

Recommend Servers

View All
Bring your real authenticated browser session to AI coding agents. Local-first MCP server + Chrome MV3 extension. No cloud. No telemetry.
@Cubenest

peek records the user's actual logged-in browser (DOM via rrweb, console events, network metadata, optional response bodies via opt-in Deep capture) through a Chrome MV3 extension. The extension ships events through a native-messaging stdio bridge to a local MCP server (peek-mcp), which persists them to a SQLite database at ~/.peek/sessions.db. AI coding agents (Claude Code, Cursor, Cline, Windsurf) read sessions from the database via 10 MCP tools: Tool What it does list_recent_sessions List recently recorded sessions (id, origin, ts, event count). get_session_summary LLM-readable narrative summary of a session. get_session_console_errors Console errors recorded in a session. get_session_network_errors Failed/notable network requests in a session. get_user_action_before_error Last N user actions before a console error. generate_playwright_repro Generate a runnable Playwright test from a session. get_dom_snapshot Reconstruct the DOM at a given timestamp. query_dom_history Timeline of attribute/text changes for a selector. request_authorization Side-panel consent for write actions (Level 3). execute_action Dispatch a UI action (gated by permission level + destructive blocklist). Why local-first matters Every other "browser session for AI" tool ships to a vendor cloud. peek's SQLite + extension live on the user's machine — no remote endpoints, no telemetry. The privacy policy (docs/peek/PRIVACY_POLICY.md) is the source of truth. Install # 1. Add the MCP server to Claude Code claude mcp add peek -- npx -y @peekdev/mcp # 2. Install the Chrome extension from the Chrome Web Store # (link added once the CWS listing is approved)

a day ago