Baseline Defenses for Adversarial Attacks Against Aligned Language Models

How Chatbots Get Tricked — Simple Ways to Block Jailbreaks

Big language models are showing up everywhere, and some people try to trick them with clever prompts.
Attackers use prompts called jailbreaking to make models ignore rules and bypass moderation, so that's a real worry.
Researchers tried simple protections: spot odd text, clean up the input, or teach models by showing bad prompts.
These three kinds of defenses work sometimes, and other times they dont, because the tricks keep changing.
The tests found that making strong attacks is often slow and pricey, so the cost of an attack matters a lot.
Simple filters and rewording input can stop many attempts, yet not every one, and models seems to handle some attacks better than expected.
We still dont know if smarter tools will appear or if basic fixes will hold.
People building chatbots should watch this space, patch up holes, and expect more clever tricks in the near future.

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Baseline Defenses for Adversarial Attacks Against Aligned Language Models

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