Adversarial Robustness & Jailbreak Defense Architectures

Uses hundreds of in-context dialogue turns or benign framing to gradually bypass safety guardrails without triggering threshold filters.

Hides malicious instructions inside external websites, PDF documents, or database records ingested by autonomous agent tools.

Appends mathematically optimized token noise that causes internal attention activations to override safety refusal heads.

An unprivileged parser LLM processes external web content and returns strictly validated JSON schemas to the privileged decision LLM.

Requires HMAC signatures and human approval tokens for irreversible destructive API calls (financial transfers, database deletes).

Directly monitors internal SAE feature vectors to detect malicious intent before tokens are generated.

Autonomous agents iteratively explore model vulnerabilities, generating novel exploits and reporting security regressions.

Rapidly synthesizes adversarial examples into fine-tuning datasets to harden models against newly discovered zero-day exploits.

Runs all agent code execution inside ephemeral, network-isolated WebAssembly or gVisor container sandboxes.