Research

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Kaspersky’s new global research reveals challenges behind limited family conversations on the internet safety

A look at generative AI and how its development so far defies some common assumptions, as well as where it’s likely to go from here.

The jailbreak technique "Bad Likert Judge" manipulates LLMs to generate harmful content using Likert scales, exposing safety gaps in LLM guardrails.

Learn about obfuscation and token smuggling in prompt hacking. These techniques bypass filters by replacing or encoding sensitive words, making attacks harder to detect.

Recent explorations with commercial Large Language Models (LLMs) have shown that non-expert users can jailbreak LLMs by simply manipulating their prompts; resulting in degenerate output behavior, privacy and security breaches, offensive outputs, and violations of content regulator policies. Limited studies have been conducted to formalize and analyze these attacks and their mitigations. We bridge this gap by proposing a formalism and a taxonomy of known (and possible) jailbreaks. We survey existing jailbreak methods and their effectiveness on open-source and commercial LLMs (such as GPT-based models, OPT, BLOOM, and FLAN-T5-XXL). We further discuss the challenges of jailbreak detection in terms of their effectiveness against known attacks. For further analysis, we release a dataset of model outputs across 3700 jailbreak prompts over 4 tasks.

Large Language Models (LLMs) are increasingly being integrated into various applications. The functionalities of recent LLMs can be flexibly modulated via natural language prompts. This renders them susceptible to targeted adversarial prompting, e.g., Prompt Injection (PI) attacks enable attackers to override original instructions and employed controls. So far, it was assumed that the user is directly prompting the LLM. But, what if it is not the user prompting? We argue that LLM-Integrated Applications blur the line between data and instructions. We reveal new attack vectors, using Indirect Prompt Injection, that enable adversaries to remotely (without a direct interface) exploit LLM-integrated applications by strategically injecting prompts into data likely to be retrieved. We derive a comprehensive taxonomy from a computer security perspective to systematically investigate impacts and vulnerabilities, including data theft, worming, information ecosystem contamination, and other novel security risks. We demonstrate our attacks' practical viability against both real-world systems, such as Bing's GPT-4 powered Chat and code-completion engines, and synthetic applications built on GPT-4. We show how processing retrieved prompts can act as arbitrary code execution, manipulate the application's functionality, and control how and if other APIs are called. Despite the increasing integration and reliance on LLMs, effective mitigations of these emerging threats are currently lacking. By raising awareness of these vulnerabilities and providing key insights into their implications, we aim to promote the safe and responsible deployment of these powerful models and the development of robust defenses that protect users and systems from potential attacks.

Learn Prompting is the largest and most comprehensive course in prompt engineering available on the internet, with over 60 content modules, translated into 9 languages, and a thriving community.

Learn Prompting is the largest and most comprehensive course in prompt engineering available on the internet, with over 60 content modules, translated into 9 languages, and a thriving community.

Learn Prompting is the largest and most comprehensive course in prompt engineering available on the internet, with over 60 content modules, translated into 9 languages, and a thriving community.

Learn Prompting is the largest and most comprehensive course in prompt engineering available on the internet, with over 60 content modules, translated into 9 languages, and a thriving community.

The misuse of large language models (LLMs) has drawn significant attention from the general public and LLM vendors. One particular type of adversarial prompt, known as jailbreak prompt, has emerged as the main attack vector to bypass the safeguards and elicit harmful content from LLMs. In this paper, employing our new framework JailbreakHub, we conduct a comprehensive analysis of 1,405 jailbreak prompts spanning from December 2022 to December 2023. We identify 131 jailbreak communities and discover unique characteristics of jailbreak prompts and their major attack strategies, such as prompt injection and privilege escalation. We also observe that jailbreak prompts increasingly shift from online Web communities to prompt-aggregation websites and 28 user accounts have consistently optimized jailbreak prompts over 100 days. To assess the potential harm caused by jailbreak prompts, we create a question set comprising 107,250 samples across 13 forbidden scenarios. Leveraging this dataset, our experiments on six popular LLMs show that their safeguards cannot adequately defend jailbreak prompts in all scenarios. Particularly, we identify five highly effective jailbreak prompts that achieve 0.95 attack success rates on ChatGPT (GPT-3.5) and GPT-4, and the earliest one has persisted online for over 240 days. We hope that our study can facilitate the research community and LLM vendors in promoting safer and regulated LLMs.

==Welcome to Q Research General=='''We are researchers who deal in open-source information, reasoned argument, and dank memes. We do battle in the sphere of ideas and ideas only. We neither need nor condone the use of force in our work here.'''''"We hold these truths to be self-evident: that all men are created equal; that they are endowed by their Creator with certain unalienable rights; that among these are life, liberty, and the pursuit of happiness.'''==VINCIT OMNIA VERITAS | SEMPER FIDELIS | WWG1WGA | QRESEARCH====Q's Latest Posts==>>18284019 Nov. - Dec. 2022==Q's Private Board==>>>/projectdcomms/ & '''Q's Trip-code:''' Q !!Hs1Jq13jV6==Find Q drops here==Qresear.ch/q-posts, Qanon.pub, Qalerts.pub, OperationQ.pub. Qposts.online, 8kun.top/qresearch/, Qalerts.app, Qalerts.net, douknowq.com/134295/Q-Anon-Pub.htm8ku==Q Posts Archives=='''* Q Map & Mirrors PDF:''' SCRIBD: https:''//''www.scribd.com/document/419874308/Q-Anon-The-Storm-X-VII?secret_password=55SQ1tCYhuNR8ESzm50u'''* Q Posts Archive, Searchable, interactive with user-explanations:''' qanon.pub qanon.app'''* Q Posts Archive + RSS, Searchable, Analytics, Offsite Bread Archive:''' qanon.news'''* Q Raw Text Dumps:''' q-clock.com/q_raw.txt'''* Q Original, full-size images Q has posted:''' https:''//''postimg.cc/gallery/29wdmgyze/'''* Q Research Memo & OIG Report Links:''' 8kun.top/qresearch/res/426641.html#427188'''* Q Research Notables:''' Archive Board >>>/qnotables/'''* Q Adjacent infographs and moar:''' https:''//''deepstatemappingproject.com/==Q Research Board==Key Resources below. Check DOUGH RESOURCES thread for more: >>17225239'''New to QR?'''>>17240320 Welcome to Q Research | >>20424387 Board Info '''Meme Warfare'''MEME WARRIOR UI 1.3 #240904: https:''//''archive.is/3Pe0E'''Board History'''>>17242392 Q Encyclopedia & >>17242386 Q Video by Archive Anon'''TOR Access'''__TOR URL__: http:''//''w7m432cocr665kf5tlpcxojwldajr3njd2etcxwhpbrt44eemuxhp7ad.onion/qresearch/catalog.html__TOR Banner__: https:''//''www.youtube.com/watch?v=MLCupx1UExg

==Welcome to Q Research General=='''We are researchers who deal in open-source information, reasoned argument, and dank memes. We do battle in the sphere of ideas and ideas only. We neither need nor condone the use of force in our work here.'''''"We hold these truths to be self-evident: that all men are created equal; that they are endowed by their Creator with certain unalienable rights; that among these are life, liberty, and the pursuit of happiness.'''==VINCIT OMNIA VERITAS | SEMPER FIDELIS | WWG1WGA | QRESEARCH====Q's Latest Posts==>>18284019 Nov. - Dec. 2022==Q's Private Board==>>>/projectdcomms/ & '''Q's Trip-code:''' Q !!Hs1Jq13jV6==Find Q drops here==Qresear.ch/q-posts, Qanon.pub, Qalerts.pub, OperationQ.pub. Qposts.online, 8kun.top/qresearch/, Qalerts.app, Qalerts.net, douknowq.com/134295/Q-Anon-Pub.htm8ku==Q Posts Archives=='''* Q Map & Mirrors PDF:''' SCRIBD: https:''//''www.scribd.com/document/419874308/Q-Anon-The-Storm-X-VII?secret_password=55SQ1tCYhuNR8ESzm50u'''* Q Posts Archive, Searchable, interactive with user-explanations:''' qanon.pub qanon.app'''* Q Posts Archive + RSS, Searchable, Analytics, Offsite Bread Archive:''' qanon.news'''* Q Raw Text Dumps:''' q-clock.com/q_raw.txt'''* Q Original, full-size images Q has posted:''' https:''//''postimg.cc/gallery/29wdmgyze/'''* Q Research Memo & OIG Report Links:''' 8kun.top/qresearch/res/426641.html#427188'''* Q Research Notables:''' Archive Board >>>/qnotables/'''* Q Adjacent infographs and moar:''' https:''//''deepstatemappingproject.com/==Q Research Board==Key Resources below. Check DOUGH RESOURCES thread for more: >>17225239'''New to QR?'''>>17240320 Welcome to Q Research | >>20424387 Board Info '''Meme Warfare'''MEME WARRIOR UI 1.3 #240904: https:''//''archive.is/3Pe0E'''Board History'''>>17242392 Q Encyclopedia & >>17242386 Q Video by Archive Anon'''TOR Access'''__TOR URL__: http:''//''w7m432cocr665kf5tlpcxojwldajr3njd2etcxwhpbrt44eemuxhp7ad.onion/qresearch/catalog.html__TOR Banner__: https:''//''www.youtube.com/watch?v=MLCupx1UExg

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This dataset contains all job applications submitted through the Borough Offices, through eFiling, or through the HUB, which have a "Latest Action Date" since January 1, 2000. This dataset does not include jobs submitted through DOB NOW. See the DOB NOW: Build – Job Application Filings dataset for DOB NOW jobs.

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Clickjacking ist eine Technik, bei der ein Computerhacker die Darstellung einer Internetseite überlagert und dann deren Nutzer dazu veranlasst, scheinbar harmlose Mausklicks und/oder Tastatureingaben durchzuführen.