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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nono
nono is an open source, kernel-enforced sandbox for AI coding agents and LLM workloads. Unlike policy-based guardrails that intercept and filter operations, nono uses OS security primitives — Landlock on Linux and Seatbelt on macOS — to make unauthorised operations structurally impossible at the syscall level.
Wrap any AI agent — Claude Code, OpenCode, OpenClaw, or any CLI process — with a single command. nono applies default-deny filesystem access, blocks destructive commands (rm, dd, chmod, sudo), isolates credentials and API keys, and cascades all restrictions to child processes. No escape mechanism exists once restrictions are applied.
Built-in profiles get you running in seconds. Secrets inject securely from the system keystore and are zeroised on exit. Audit logging, atomic rollbacks, and Sigstore-attested policy signing are on the roadmap.
Apache 2.0. From the creator of Sigstore.
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Constellation Gate AI
Constellation Gate AI is a drop-in defense layer for AI agents, built to sit between the agent and the model while screening every request for attacks and leaks. Gate acts as an inline gateway for coding agents and model APIs, protecting workflows without requiring major code changes. Users can point existing tools such as Claude Code, Cursor, OpenClaw, Codex, or OpenCode at Gate and inherit prompt-injection defense, secret scanning, PII redaction, token optimization, and a verifiable audit trail. The platform is designed around three real risks: prompt injection, credential and PII leakage, and hijacked tool calls. Instead of relying on the model to defend itself, Gate blocks attacks before they reach the model, redacts secrets before responses return, and stops attacker-controlled tool outputs before an agent acts on them. Gate accepts the same calls an agent already makes, forwards them to the model, scans every call and response in both directions.
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Cortex Agentic Endpoint Security
Palo Alto Networks Cortex Agentic Endpoint Security (AES) is an AI-native endpoint security platform designed to protect enterprise devices from risks associated with autonomous AI agents and modern software applications. The platform continuously discovers AI agents, local models, browser extensions, IDE plugins, Model Context Protocol (MCP) servers, and other software components operating on endpoints. Its context-aware risk analysis evaluates software dependencies, permissions, behaviors, and potential security exposures to help organizations prioritize threats. Cortex AES provides automated governance policies and security guardrails that control agent interactions and restrict potentially unsafe software. Its real-time prevention capabilities block malicious agent actions, prompt injection attacks, unauthorized data access, and risky software execution before they cause damage.
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