Hey Product Hunt! Mattijs here, the founder of SovereignShield. I'm a security engineer, and I originally built this because I was genuinely terrified of the way the industry is deploying autonomous AI agents right now. Currently, if an LLM hallucinates a catastrophic medical dosage or executes a bad API call, the industry standard is to put another LLM in front of it to double-check the output. I call this "Risk Laundering." You are replacing one probability with another probability. If you are building AI for regulated industries (healthcare, fintech, industrial), probabilistic safety is a non-starter. You can't tell your legal team or a regulator that your AI guessed an action was 90% safe. You need mathematical guarantees. So, I built SovereignShield: a 7-layer deterministic defense suite. It stops prompt injections, jailbreaks, and hallucinations not by asking another model to be smart, but by enforcing pure mathematical rules and OS-level memory protection. How it works under the hood: Instead of trusting the LLM, SovereignShield locks the agent's safe environment (schemas, tool capabilities, and permissions) into a FrozenNamespace at the Python metaclass level. We then use OS-level memory protection (mprotect/VirtualProtect) to freeze those security constants in hardware so even an attacker with code execution cannot modify them. The 7-layer suite includes: InputFilter (Deterministic keyword filtering across 20+ languages) AdaptiveShield (Self-learning keyword engine) Conscience (Ethical boundary verification) CoreSafety (Hardware-protected immutability) HITLApproval (Human-in-the-loop pausing for high-risk actions) MultiModalFilter (Binary file/upload validation) TruthGuard (Tracking factual hallucinations against tool execution) It's entirely open-core (BSL 1.1) and handles the verification deterministically in sub-millisecond times with zero dependencies. I would absolutely love for you to try it out, poke holes in the architecture, and let me know below how you are currently handling liability, hallucinations, and prompt injection in your own AI/agent deployments. Happy to answer any technical questions you have about deterministic validation or the architecture!

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5mo ago

How is everyone handling prompt injection in autonomous agents right now?

Hi everyone! I'm Mattijs, and I'm launching SovereignShield tomorrow (a 7-layer deterministic defense suite for AI systems).

I built it because having LLMs grade other LLMs for safety feels like risk laundering to me, especially when you are giving agents access to APIs and databases.

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SovereignShield

Immutable deterministic security architecture for AI systems

Immutable deterministic security architecture for AI systems

Forum Threads

How is everyone handling prompt injection in autonomous agents right now?

Forum Threads

How is everyone handling prompt injection in autonomous agents right now?