[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-31803":3,"doc-seo-31803":27},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"file_id":15,"file_url":16,"file_type":17,"file_size":18,"view_count":4,"is_deleted":4,"is_public":19,"is_downloadable":19,"audit_status":19,"page_count":20,"language":21,"language_code":22,"table_of_contents":23,"faqs":24,"seo_title":13,"seo_description":14,"update_tm":25,"read_time":26},31803,2336464648322,"Aria","https://ap-avatar.wpscdn.com/avatar/2200025388227c56fec?_k=1778556882303663488",8,"Research & Report","Prevention of Prompt Injection Attacks Over Financial Applications Integrated with LLM","Prompt injection is a growing threat to financial applications that integrate Large Language Models. By manipulating user prompts, attackers can trigger unintended outputs, leading to data breaches, confidential data loss, and direct financial loss. Existing defenses such as input/output filtering and delimiters have proven insufficient. The paper proposes an enhanced security system that adds role-based access control, jailbreak attack detection, input validation, and secure prompt passing. It uses a preprocessing layer on both client and LLM sides to identify critical and destructive keywords, blocking malicious prompts so only authenticated and authorized commands proceed.","cbCaifvkbrNARhnv","https://ap.wps.com/l/cbCaifvkbrNARhnv","pdf",1053967,1,6,"English","en","# Introduction\n## Threat of prompt injection in finance\n## Limitations of conventional defenses\n# Secure interaction and overview\n# Proposed enhanced security system","[{\"question\":\"What risk do prompt injection attacks create in LLM-integrated financial applications?\",\"answer\":\"They manipulate input prompts to induce unintended or harmful outputs, which can cause data breaches, confidential data loss, and financial losses through unauthorized actions.\"},{\"question\":\"Why are existing defense techniques like filtering and delimiters considered inadequate?\",\"answer\":\"The paper states that such measures have been proven inadequate for effectively mitigating prompt injection attacks in these financial systems.\"},{\"question\":\"What main components does the proposed security system add to reduce prompt injection attacks?\",\"answer\":\"It introduces role-based access, jailbreak detection, input validation, and secure prompt handling, implemented via a preprocessing layer on both the client and LLM sides to detect critical and destructive keywords.\"}]",1780174846,15,{"code":4,"msg":28,"data":29},"ok",{"site_id":30,"language":22,"slug":31,"title":13,"keywords":32,"description":14,"schema_data":33,"social_meta":84,"head_meta":86,"extra_data":88,"updated_unix":25},105,"prevention-of-prompt-injection-attacks-over-financial-applications-integrated-with-llm","",{"@graph":34,"@context":83},[35,52,66],{"@type":36,"itemListElement":37},"BreadcrumbList",[38,42,46,49],{"item":39,"name":40,"@type":41,"position":19},"https://docshare.wps.com","Home","ListItem",{"item":43,"name":44,"@type":41,"position":45},"https://docshare.wps.com/document/","Document",2,{"item":47,"name":12,"@type":41,"position":48},"https://docshare.wps.com/document/research-report/",3,{"item":50,"name":13,"@type":41,"position":51},"https://docshare.wps.com/document/prevention-of-prompt-injection-attacks-over-financial-applications-integrated-with-llm/31803/",4,{"url":50,"name":13,"@type":53,"author":54,"headline":13,"publisher":56,"fileFormat":59,"description":14,"dateModified":60,"datePublished":60,"encodingFormat":59,"isAccessibleForFree":61,"interactionStatistic":62},"DigitalDocument",{"name":9,"@type":55},"Person",{"url":39,"name":57,"@type":58},"DocShare","Organization","application/pdf","2026-05-30",true,{"@type":63,"interactionType":64,"userInteractionCount":4},"InteractionCounter",{"@type":65},"ViewAction",{"@type":67,"mainEntity":68},"FAQPage",[69,75,79],{"name":70,"@type":71,"acceptedAnswer":72},"What risk do prompt injection attacks create in LLM-integrated financial applications?","Question",{"text":73,"@type":74},"They manipulate input prompts to induce unintended or harmful outputs, which can cause data breaches, confidential data loss, and financial losses through unauthorized actions.","Answer",{"name":76,"@type":71,"acceptedAnswer":77},"Why are existing defense techniques like filtering and delimiters considered inadequate?",{"text":78,"@type":74},"The paper states that such measures have been proven inadequate for effectively mitigating prompt injection attacks in these financial systems.",{"name":80,"@type":71,"acceptedAnswer":81},"What main components does the proposed security system add to reduce prompt injection attacks?",{"text":82,"@type":74},"It introduces role-based access, jailbreak detection, input validation, and secure prompt handling, implemented via a preprocessing layer on both the client and LLM sides to detect critical and destructive keywords.","https://schema.org",{"og:url":50,"og:type":85,"og:title":13,"og:site_name":57,"og:description":14},"article",{"robots":87,"canonical":50},"index,follow",{"doc_id":7,"site_id":30}]