Research
Security for agents starts where reasoning becomes action.
GuardPrompt is based on a simple thesis: autonomous agents may reason dynamically, but their operational behavior must remain bounded, testable, certifiable, and enforceable.
Identity is necessary, but not sufficient
Agent identity tells us who the agent is. GuardPrompt focuses on whether the agent's behavior remains within approved operational boundaries.
The harness is the new attack surface
Agent behavior emerges from prompts, tools, memory, orchestration, context, and runtime state. Security must validate the harness, not just the model.
Behavior contracts as deployment controls
AI agents should carry machine-readable contracts describing tools, data access, delegation, memory, approvals, and runtime limits.
Certificates for agentic systems
Before production access, agents should produce evidence that their implementation was tested against approved behavioral expectations.
Core philosophy
Govern actions, not thoughts.
GuardPrompt does not attempt to constrain every internal reasoning path of an AI agent. Instead, it focuses on governing the transition from cognition to action: tool calls, API requests, memory writes, delegation, data access, and production workflow execution.
Operating principles
From static controls to behavioral assurance.
Traditional security controls assume predictable software behavior. Autonomous agents introduce adaptive behavior shaped by context, prompts, tools, memory, and dynamic orchestration. GuardPrompt treats agent behavior as something that must be continuously validated against explicit operational boundaries.
Reasoning Layer ↓ Intent / Plan ↓ Behavior Contract Validation ↓ Policy Decision ↓ Tool or API Execution ↓ Evidence + Drift Monitoring