AI Security Guard
AI Security Guard is a multi-faceted platform for securing autonomous AI, combining a protection SDK, product tooling, education, and original research on the agentic future.
- Protection SDK: Integration-friendly API wrapper designed to shield AI agents from jailbreaks, prompt injection, and other harmful content before it reaches your models.
- AgentGuard360: Built on the API: Intercepts AI traffic in real time before malicious content reaches your agents. Two-tier content scanning, supply chain protection, and device hardening in one tool. Privacy-first: Content stays local unless you request premium analysis.
- Research: Original analysis on the autonomous AI future and the security, privacy, and safety issues that follow, including reports like Shipping the Future.
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Qwen3.8-Max
Qwen3.8-Max is Qwen’s most capable model to date, built as a Max-class AI model for coding, work, research, long-horizon tasks, and multimodal agents. It scales to 2.4 trillion parameters with 95 billion active parameters and is available through QwenCloud. The model is designed to complete complex, open-ended tasks end to end with greater reliability and minimal human involvement. Qwen3.8-Max supports autonomous coding workflows, agentic development, research reproduction, visual reasoning, document understanding, video analysis, and real-world productivity tasks. It can integrate with popular agent frameworks and coding assistants, including Claude Code, Codex, Qoder CLI, Qwen Code, and OpenClaw. Built for developers, researchers, enterprises, and AI agent builders, Qwen3.8-Max helps teams automate sophisticated work across code, documents, tools, interfaces, and multimodal content.
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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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Kastra
Kastra is the authorization layer for AI systems, deciding what agents, models, and AI tools are allowed to do before they do it. It sits in the execution path of every prompt, tool call, shell command, database operation, and API request, evaluates each action against deterministic, attribute-based policy, and returns an allow, deny, redact, or escalate decision in under a millisecond. Unlike monitoring products that observe AI after it acts, Kastra blocks unauthorized behavior before it reaches a tool, API, database, or production system. Its unified control plane combines a policy engine, edge decision points, integrations, and a tamper-evident evidence vault that signs every decision for audit and replay. Kastra Edge brings local enforcement to developer machines, protecting Claude Code, Cursor, Codex CLI, and other coding agents from destructive commands, secret exfiltration, unsafe file writes, and unauthorized tool use.
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