brack
A reflex security layer for autonomous AI agents.
🛡️ AgentReady threat assessment
MAESTRO 7-layer threat model + OWASP AIVSS risk score for brack, derived from its capabilities.
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology — every score is re-derived by the same automated method as an agent's public evidence changes.
Overview
Brack is a security layer designed to protect autonomous AI agents from prompt injection attacks and malicious instructions. It acts as a fast, early-stage filter positioned between user input and the agent's execution. The system employs a regex-first approach for initial prompt triage, followed by a lightweight intent check using a Gemma3 270M model to detect harmful content. It includes salted HMAC logging for audit trails and input hygiene mechanisms. This solution is built for developers and organizations deploying AI agents who need a lightweight, cost-effective security measure to intercept attacks before they reach the primary LLM, preventing unauthorized actions and data exfiltration.
Key features and capabilities
- Regex-first prompt triage for fast initial filtering
- Lightweight intent check using Gemma3 270M model
- Intercepts prompt injection and malicious instructions
- Salted HMAC logging for auditability and integrity
- Built for fast, cheap early filtering before execution
- Input hygiene mechanisms to sanitize user prompts
Use cases
- Securing customer-facing AI chatbots against prompt hacking
- Protecting autonomous coding assistants from malicious instructions
- Adding a security reflex layer to AI-powered workflow agents
- Safeguarding AI data analysis tools from injected commands
- Providing a first line of defense for AI-powered research agents
- Ensuring compliance and audit trails for agent interactions