The industry keeps getting agentic security wrong, so I developed a free platform to teach what actually works

Reddit r/AI_Agents Tools
agentic-ai security prompt-injection training educational-tool

Summary

The article introduces Tantalus, a free platform for learning how to secure agentic AI systems against indirect prompt injection and data exfiltration through realistic challenges.

If you’re like me, you’re tired of AI security training that lacks practical experience. How will asking a chatbot to say a bad word prepare you for building and securing real production agentic systems? I have been frustrated with how the industry approaches AI security, often neglecting to teach not only how to break AI agents but, crucially, how to fix them. That’s why I created the Indirect Prompt Injection Arena: Tantalus. The premise is straightforward: instead of telling players to "jailbreak" a chatbot by getting it to break character, I designed Tantalus to be a REALISTIC environment where players work to get an AI assistant to exfiltrate data from a user’s workstation. Getting an agent to say a bad word only harms humans. However, getting an agent to perform an unauthorized action, such as emailing your secrets to a threat actor, is a different story. This represents a genuine breach in the security of your agentic systems. Tantalus features a two-round arena that places players in front of a realistic AI assistant with access to files, emails, and chat history, pre-loaded with both legitimate and poisoned tools. In Round 1, players will encounter three industry-standard guardrails that they must overcome. Round 2 introduces a brutal twist: the ONLY available data for the agent is the poisoned data. Yes, Round 2 presents a deliberately vulnerable agent that is guaranteed to be prompt-injected. So, what’s the twist? All Round 1 guardrails are removed and replaced with a single control within the model's generation stream. This control has a proven 100% success rate at preventing data exfiltration. This statistic is not only supported by my research, but the platform itself, as it has seen zero players win in Round 2. If you want to learn how real-world agentic systems fail under pressure and how to secure them, check out Tantalus for a free, hands-on experience that is both educational and engaging.
Original Article

Similar Articles

Understanding prompt injections: a frontier security challenge

OpenAI Blog

OpenAI publishes guidance on prompt injection attacks, a social engineering vulnerability where malicious instructions hidden in web content or documents can trick AI models into unintended actions. The company outlines its multi-layered defense strategy including instruction hierarchy research, automated red-teaming, and AI-powered monitoring systems.

Insights on Indirect Prompt Injection (12 minute read)

TLDR AI

Zico Kolter and Matt Fredrikson, leaders at Gray Swan and experts in AI security, discuss the state of AI red-teaming and indirect prompt injection, a critical vulnerability for AI agents. They explain why AI security requires a different mindset, how automated red-teaming can beat humans, and introduce tools like Shade for adversarial testing.

Free AI Agent Security Assessment

Reddit r/AI_Agents

Antitech is offering free early-access security assessments for AI agents, testing against attack vectors like prompt injection, tool abuse, and data leakage, providing a vulnerability report and discounts for participants.

Designing AI agents to resist prompt injection

OpenAI Blog

OpenAI publishes guidance on designing AI agents resistant to prompt injection attacks, arguing that modern attacks increasingly use social engineering tactics rather than simple string injections, and advocating for system-level defenses that constrain impact rather than relying solely on input filtering.