Stop AI agents from doing things they shouldn't. The action authorization layer — pre-execution, deterministic, policies included. Drop in. Day one.
Open protocol and TypeScript SDK for AI agent authority: identity, scoped delegation, enforcement before the action, and signed receipts.
A cognition kernel that wraps a frozen LLM in a persistent identity + trust + governance loop — testing whether capability comes from structure, not weights. Research-stage; honest about what's real vs mocked.
The authorization kernel for AI agents. Block, allow, or escalate agent tool calls with YAML rules — deterministic-first, LLM fallback.
Deterministic execution authorization for AI agents and automation systems
Deterministic authorization + tamper-evident audit for AI agents, humans, and workloads — one principal type, safety invariants machine-checked by an SMT solver (cvc5), every decision independently verifiable offline. Pure Rust.
Web4: an open standard for verifiable AI presence — LCT identity, T3/V3 trust tensors, MRH context, ATP/ADP. Rust + Python SDKs on crates.io/PyPI. AGPL-3.0-or-later.
TrapDefense — Open-source AI Security Gateway for HTTP APIs and MCP tools. Inspect content, enforce agent permissions, and audit decisions.
Authorization, delegation, provenance, and verifiable-audit engine for AI agents. MCP adapter published.
Jev agent authorization for MCP tool calls: Kinde identity and permissions plus Jev's typed, calibrated decisions, checked server-side before every call runs
Hestia — universal Web4 presence for humans and AI. Local-first cryptographic identity, encrypted vault, delegation authority, witnessed trust record, and device constellation. Cross-platform app + AI plugin + CLI. EUDI-compatible credential issuance. AGPL-3.0.
Language-neutral authorization and governance framework for AI agents, Spring AI, and Model Context Protocol (MCP)
Draco-Tech is the identity and authorization layer that lets autonomous agents operate with zero static credentials and full policy adherence.
Runtime guardrails for TypeScript AI agents. Prevents duplicate tool calls, enforces per-user cost budgets, and gates irreversible actions. MIT.
Permissions that narrow when one AI agent delegates: a sub-agent never holds more than its parent. In-process, with a hash-chained audit log you verify offline. Python and TypeScript, adapters for 19 frameworks and A2A.
A dual-authorization layer for AI agents with independent approvals, single-use capability tokens, auditability, and fail-closed execution.
Aiyo Execution Authorization Protocol — open specification for runtime execution authorization of autonomous agents.
Attenu Derive: computes the permission set each AI agent task needs from the app itself — roster, tools, observed calls — for attenu-guard to enforce on every tool call and sub-agent handoff.
Watch AI agents get stopped. Runnable references for Ratify Protocol: a principal signs a bounded mandate, and the system carrying the consequence verifies it before acting.
Deterministic pre-execution policy for AI agent tool calls in Go.
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