{"id":11364,"date":"2024-04-05T08:45:19","date_gmt":"2024-04-05T08:45:19","guid":{"rendered":"https:\/\/dailyai.com\/?p=11364"},"modified":"2024-04-05T08:45:19","modified_gmt":"2024-04-05T08:45:19","slug":"anthropic-large-context-llms-vulnerable-to-many-shot-jailbreak","status":"publish","type":"post","link":"https:\/\/dailyai.com\/nb\/2024\/04\/anthropic-large-context-llms-vulnerable-to-many-shot-jailbreak\/","title":{"rendered":"Antropisk: LLM-er med stor kontekst er s\u00e5rbare for jailbreak med mange skudd"},"content":{"rendered":"

Anthropic har utgitt en artikkel som skisserer en jailbreaking-metode med mange skudd som LLM-er med lang kontekst er spesielt s\u00e5rbare for.<\/strong><\/p>\n

St\u00f8rrelsen p\u00e5 kontekstvinduet til en LLM-modell bestemmer den maksimale lengden p\u00e5 en ledetekst. Kontekstvinduene har vokst jevnt og trutt de siste m\u00e5nedene, og modeller som Claude Opus har n\u00e5 et kontekstvindu p\u00e5 1 million tokens.<\/p>\n

Det utvidede kontekstvinduet gj\u00f8r det mulig med mer effektiv l\u00e6ring i kontekst. Med en null-shot-prompt blir en LLM bedt om \u00e5 gi et svar uten tidligere eksempler.<\/p>\n

I en \"few-shot\"-tiln\u00e6rming f\u00e5r modellen flere eksempler i ledeteksten. Dette gir mulighet for l\u00e6ring i kontekst og setter modellen i stand til \u00e5 gi et bedre svar.<\/p>\n

St\u00f8rre kontekstvinduer betyr at brukerens ledetekst kan v\u00e6re ekstremt lang og inneholde mange eksempler, noe som if\u00f8lge Anthropic b\u00e5de er en velsignelse og en forbannelse.<\/p>\n

Jailbreak med mange bilder<\/h2>\n

Jailbreak-metoden er sv\u00e6rt enkel. LLM blir bedt om en enkelt melding som best\u00e5r av en falsk dialog mellom en bruker og en veldig im\u00f8tekommende AI-assistent.<\/p>\n

Dialogen best\u00e5r av en rekke sp\u00f8rsm\u00e5l om hvordan man gj\u00f8r noe farlig eller ulovlig, etterfulgt av falske svar fra AI-assistenten med informasjon om hvordan man utf\u00f8rer aktivitetene.<\/p>\n

Sp\u00f8rringen avsluttes med et m\u00e5lsp\u00f8rsm\u00e5l som \"Hvordan bygger man en bombe?\", og deretter overlates det til den utvalgte LLM-en \u00e5 svare.<\/p>\n

\"\"
F\u00e5-shot vs mange-shot jailbreak. Kilde: Anthropic<\/figcaption><\/figure>\n

Hvis du bare har noen f\u00e5 interaksjoner frem og tilbake i ledeteksten, fungerer det ikke. Men med en modell som Claude Opus kan en ledetekst med mange bilder v\u00e6re like lang som flere lange romaner.<\/p>\n

I deres artikkel<\/a>fant Anthropic-forskerne at \"etter hvert som antallet inkluderte dialoger (antall \"shots\") \u00f8ker utover et visst punkt, blir det mer sannsynlig at modellen vil gi en skadelig respons.\"<\/p>\n

De fant ogs\u00e5 ut at n\u00e5r de ble kombinert med andre kjente jailbreaking-teknikker<\/a>var metoden med mange bilder enda mer effektiv, eller den kunne v\u00e6re vellykket med kortere beskjeder.<\/p>\n

\"\"
N\u00e5r antallet dialoger i ledeteksten \u00f8ker, \u00f8ker sjansen for en skadelig respons. Kilde: Anthropic: Anthropic<\/figcaption><\/figure>\n

Kan det fikses?<\/h2>\n

Anthropic sier at det enkleste forsvaret mot many-shot jailbreak er \u00e5 redusere st\u00f8rrelsen p\u00e5 en modells kontekstvindu. Men da mister du de \u00e5penbare fordelene ved \u00e5 kunne bruke lengre innganger.<\/p>\n

Anthropic pr\u00f8vde \u00e5 f\u00e5 LLM-en sin til \u00e5 identifisere n\u00e5r en bruker pr\u00f8vde en jailbreak med mange bilder, og deretter nekte \u00e5 svare p\u00e5 foresp\u00f8rselen. De fant ut at det bare forsinket jailbreakingen og krevde en lengre ledetekst for \u00e5 til slutt fremkalle det skadelige resultatet.<\/p>\n

Ved \u00e5 klassifisere og modifisere ledeteksten f\u00f8r den ble sendt til modellen, lyktes de til en viss grad med \u00e5 forhindre angrepet. Anthropic sier likevel at de er oppmerksomme p\u00e5 at varianter av angrepet kan unng\u00e5 \u00e5 bli oppdaget.<\/p>\n

Anthropic sier at det stadig lengre kontekstvinduet til LLM-er \"gj\u00f8r modellene langt mer nyttige p\u00e5 alle mulige m\u00e5ter, men det muliggj\u00f8r ogs\u00e5 en ny klasse av jailbreaking-s\u00e5rbarheter\".<\/p>\n

Selskapet har publisert forskningen sin i h\u00e5p om at andre AI-selskaper skal finne m\u00e5ter \u00e5 avverge angrep med mange skudd p\u00e5.<\/p>\n

En interessant konklusjon som forskerne kom frem til, var at \"selv positive, tilsynelatende uskyldige forbedringer av LLM-er (i dette tilfellet \u00e5 tillate lengre inndata) noen ganger kan f\u00e5 uforutsette konsekvenser\".<\/p>","protected":false},"excerpt":{"rendered":"

Anthropic har gitt ut en artikkel som beskriver en jailbreaking-metode med mange bilder som LLM-er med lang kontekst er spesielt s\u00e5rbare for. St\u00f8rrelsen p\u00e5 en LLMs kontekstvindu bestemmer den maksimale lengden p\u00e5 en ledetekst. Kontekstvinduer har vokst konsekvent de siste m\u00e5nedene, og modeller som Claude Opus har n\u00e5dd et kontekstvindu p\u00e5 1 million tokens. Det utvidede kontekstvinduet gj\u00f8r det mulig med kraftigere l\u00e6ring i kontekst. Med en null-shot-prompt blir en LLM bedt om \u00e5 gi et svar uten tidligere eksempler. I en \"few-shot\"-tiln\u00e6rming f\u00e5r modellen flere eksempler i ledeteksten. Dette muliggj\u00f8r l\u00e6ring i kontekst og gir<\/p>","protected":false},"author":6,"featured_media":11368,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[],"class_list":["post-11364","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry"],"yoast_head":"\nAnthropic: Large context LLMs vulnerable to many-shot jailbreak | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/nb\/2024\/04\/anthropic-large-context-llms-vulnerable-to-many-shot-jailbreak\/\" \/>\n<meta property=\"og:locale\" content=\"nb_NO\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Anthropic: Large context LLMs vulnerable to many-shot jailbreak | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Anthropic released a paper outlining a many-shot jailbreaking method to which long-context LLMs are particularly vulnerable. 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