Show HN: AegisKernel – Test prompt injection attacks on AI agents in the browser (adikshatriyag-crypto.github.io)

AegisKernel has launched a browser-based platform that allows users to test prompt injection attacks on AI agents, highlighting the vulnerabilities in probabilistic large language model (LLM) guardrails. This live Threat Interception Sandbox demonstrates how deterministic capability boundaries can successfully block 100% of autonomous tool hijacking attempts in under a millisecond, showcasing the significant differences in security approaches within AI systems. The tool is particularly noteworthy for the AI/ML community as it enables researchers and developers to understand and tackle vulnerabilities in AI agents more effectively. By integrating a two-line Zero-Trust framework using AegisShield with strict security policies, users can run simulated attack vectors and observe real-time interception results. This innovative approach not only emphasizes the importance of robust security measures in AI deployment but also provides a practical resource for enhancing the integrity of AI applications against potential exploitation.