Flipping one hidden neuron in MLPs achieves 91.7% jailbreak success with white-box access to activations—safety isn't distributed, it's localized and fragile.
May 27, 2026
Summary
If you're deploying open-weight models in restricted environments, you need neuron-level monitoring. Current safety evaluations miss this attack vector entirely, making benchmarks like JailbreakBench insufficient for production risk assessment.
Why it matters
If you're deploying open-weight models in restricted environments, you need neuron-level monitoring. Current safety evaluations miss this attack vector entirely, making benchmarks like JailbreakBench insufficient for production risk assessment.
Implementation verdict
This doesn't replace existing safety testing—it exposes it as incomplete. Requires white-box access to activation maps to exploit, so black-box deployments aren't directly vulnerable. Start auditing your model's MLP neurons if you control the inference layer; add neuron-suppression tests to your eval suite now.
Sources
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