HOL Guard
HOL Guard is a local-first runtime security layer for AI agents that watches what an AI assistant is about to do and stops risky actions before they happen. It sits between the agent and the computer, evaluating supported tool calls and local artifacts for threats such as secret and credential exposure, destructive commands, prompt-injection-driven actions, malicious or changed packages, risky MCP configuration, and unsafe plugins, skills, hooks, and settings. Known threats can be blocked automatically, while ambiguous actions are paused for user approval so people remain in control. Guard runs entirely on the developer’s machine, works offline, and does not upload files, prompts, or passwords. Local checks typically complete in under 50 milliseconds and require no changes to existing code or routines. It supports coding agents including Claude Code, Cursor, Codex, Gemini CLI, OpenCode, Hermes, and OpenClaw, with tailored integrations that inspect actions before execution.
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Harden
Harden AIF is an agent endpoint security platform for AI coding agents. It evaluates supported agent tool calls before execution using the developer’s intent, session context, organisational policy, and the effect of the proposed action.
Harden helps protect against destructive commands, unauthorized access, unintended data transfers, secret exposure, privilege misuse, and other unsafe agent actions. Legitimate actions can proceed normally, sensitive data in supported flows can be safely redacted, and actions that fall outside the developer’s intent or authority are blocked before execution.
Harden works across popular coding agents and agentic development tools including Claude Code, Codex, Cursor, Antigravity CLI, Kiro, Hermes, and OpenClaw, providing a consistent security layer across the agent ecosystem.
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Preloop
Preloop is the open source AI agent control plane for agents that take real actions. It combines an MCP firewall for tool access, an AI model gateway for cost, safety, and attribution, policy-as-code with human approvals, runtime session observability, and audit trails in a single self-hostable platform. AI agents can deploy code, change infrastructure, move money, touch production data, and burn model spend in seconds, so Preloop helps teams control what agents can do, how much they spend, and which actions require human approval. It works with OpenClaw, Hermes, Claude Code, Codex CLI, Cursor, Gemini CLI, Windsurf, Cline, OpenCode, and any MCP-compatible agent or managed runtime. Access rules can inspect arguments and context, not just tool names, with CEL expressions for fine-grained conditions. Teams can start with observability, then layer in approvals and deny rules without SDKs or invasive app changes.
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Barndoor.ai
Barndoor is a data and access management layer designed to secure how artificial intelligence systems interact with enterprise data and infrastructure. It acts as a centralized control plane that governs AI agents and applications, allowing organizations to define policies, enforce access rules automatically, and maintain full visibility over how AI tools operate across business systems. Instead of relying only on traditional identity-based permissions, Barndoor introduces context-aware governance, enabling administrators to control what actions an AI agent can perform based on factors such as the user operating the agent, the system being accessed, the type of data involved, and the specific task being attempted. It evaluates every AI request in real time and enforces policies before an action is executed, preventing unsafe or unauthorized operations from reaching internal systems or modifying sensitive information.
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