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Hard Stop: Out-of-band kernel preemption for rogue AI agents

Hard Stop: Out-of-band kernel preemption for rogue AI agents

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Hard Stop: Kernel-Level Preemption and Containment for Rogue Agentic Execution Abstract: An autonomous generative AI operating in a continuous execution loop without an out-of-band Epistemic Andon Cord is an existential operational hazard. The Core Invariant: Epistemic Self-Referential Invalidation Principle: A stochastic language model cannot serve as its own deterministic safety arbiter. Formally, any internal self-evaluating safety loop composed of a probabilistic model $M$ with non-zero error rate $\epsilon > 0$ inherits compounded error probability $P(\text{error}) \ge 1 - (1 - \epsilon)^k$.

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Original publisherGitHub
Canonical URLhttps://github.com/joseluispino/hardstop
Publication timeThu, 24 Sep 2026 13:50:29 +0000
Retrieval time2026-09-24T14:05:26.716Z
Last seen2026-09-24T14:05:26.716Z
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SummaryWeSearch · cerebras-chat (WeSearch summarizer)
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ClusterQM5NpNvvlxvH · 1 stories
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Substitutes article?No — link-out required for full text

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Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.

Opening excerpt (first ~120 words) tap to expand

Hard Stop: Kernel-Level Preemption and Containment for Rogue Agentic Execution Abstract: An autonomous generative AI operating in a continuous execution loop without an out-of-band Epistemic Andon Cord is an existential operational hazard. Hard Stop introduces a dual-plane supervisory control architecture combining out-of-band Discrete Event System (DES) supervision, Synchronous Reactive (SR) sentinels, and sub-millisecond (<0.154 ms) POSIX/eBPF preemption buses—demonstrating deterministic process freezes before off-target socket traffic or unauthorized system calls traverse hypervisor boundaries. The Core Invariant: Epistemic Self-Referential Invalidation Principle: A stochastic language model cannot serve as its own deterministic safety arbiter.

Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.

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