Why prompt filters aren't enough when your AI agent has a bash shell

Hey Product Hunt! 👋 I’m Tabrez, the founder of Keter Labs and the creator of Reality Kernel.

Over the last year, we've seen a massive shift: AI models aren't just generating text anymore,they are acting as autonomous agents with access to bash shells, SSH keys, and internal APIs.

The security industry's response has been to build "better prompt filters" or use LLMs-as-a-judge. But when a deterministic agent is handed the keys to your infrastructure, probabilistic security is a massive liability. A prompt filter can be easily bypassed by novel jailbreaks or even a language it hasn't been trained on.

That’s why we built Reality Kernel.

We operate on a completely different thesis: We don't read the prompt; we simulate the consequences.

Instead of trying to guess an agent's intent, Reality Kernel physically intercepts the compiled OS-level system command. Before the command ever executes, we simulate its downstream trajectory across your filesystem, network stack, and privilege graph in an isolated "shadow world".

If the trajectory violates your security policies, like attempting an SSRF attack, triggering a TOCTOU race condition, or exfiltrating data via DNS, the action is blocked deterministically at the OS boundary.

🔒 Key Features:

• Sub-millisecond fast-path latency: Read-only verbs and allowlisted binaries clear instantly.

• Tamper-Evident Audit Ledger: Every ALLOW, WARN, and BLOCK verdict is cryptographically sealed into a chained SHA-256 ledger (built for SOC 2 and EU AI Act compliance).

• Language-Agnostic: Because we intercept at the kernel level, we stop attacks regardless of what language or jailbreak the attacker used to trick the LLM.

We are currently in private Alpha and are actively onboarding security engineers and AI platform teams.

I’ll be hanging out in the comments all day! I’d love to hear your thoughts, feedback, and questions. How is your team currently securing autonomous agents? Let’s chat! 👇