[{"data":1,"prerenderedAt":546},["ShallowReactive",2],{"blog-tag-en-llm-security":3},[4,80,151,207,279,362,413,509],{"slug":5,"published":6,"minutes":7,"category":8,"tags":9,"tagPages":15,"keywords":18,"about":31,"sources":39,"cover":70,"og":71,"expertise":72,"locales":73,"lang":74,"title":77,"description":78,"coverAlt":79},"llm-output-guardrails-moderation","2026-10-17",13,"security",[10,11,12,13,14],"LLM security","Guardrails","Content moderation","OWASP","Output validation",[16,17],"llm-security","guardrails",[19,20,21,22,23,24,25,26,27,28,29,30],"llm output guardrails","improper output handling llm","owasp llm05","openai moderation api","omni-moderation-latest","llama guard 4","nemo guardrails streaming","markdown image exfiltration","sanitize llm output html","groundedness detection","llm content moderation production","output rails",[32,34,37],{"name":12,"url":33},"https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FContent_moderation",{"name":35,"url":36},"Cross-site scripting","https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FCross-site_scripting",{"name":13,"url":38},"https:\u002F\u002Fowasp.org\u002F",[40,43,46,49,52,55,58,61,64,67],{"title":41,"url":42},"OWASP GenAI Security Project: LLM05:2025 Improper Output Handling","https:\u002F\u002Fgenai.owasp.org\u002Fllmrisk\u002Fllm052025-improper-output-handling\u002F",{"title":44,"url":45},"OpenAI API Docs: Moderation","https:\u002F\u002Fplatform.openai.com\u002Fdocs\u002Fguides\u002Fmoderation",{"title":47,"url":48},"Meta: Llama Guard 4 model card and prompt formats","https:\u002F\u002Fwww.llama.com\u002Fdocs\u002Fmodel-cards-and-prompt-formats\u002Fllama-guard-4\u002F",{"title":50,"url":51},"NVIDIA NeMo Guardrails: Output rail streaming configuration","https:\u002F\u002Fdocs.nvidia.com\u002Fnemo\u002Fguardrails\u002Fconfigure-guardrails\u002Fyaml-schema\u002Fstreaming\u002Foutput-rail-streaming.md",{"title":53,"url":54},"Microsoft Learn: Prompt Shields in Azure AI Content Safety","https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fazure\u002Fai-services\u002Fcontent-safety\u002Fconcepts\u002Fjailbreak-detection",{"title":56,"url":57},"Microsoft Learn: Groundedness detection in Azure AI Content Safety","https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fazure\u002Fai-services\u002Fcontent-safety\u002Fconcepts\u002Fgroundedness",{"title":59,"url":60},"Microsoft Learn: Protected material detection in Azure AI Content Safety","https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fazure\u002Fai-services\u002Fcontent-safety\u002Fconcepts\u002Fprotected-material",{"title":62,"url":63},"Guardrails AI documentation","https:\u002F\u002Fwww.guardrailsai.com\u002Fdocs",{"title":65,"url":66},"Vue.js docs: Security best practices","https:\u002F\u002Fvuejs.org\u002Fguide\u002Fbest-practices\u002Fsecurity.html",{"title":68,"url":69},"Simon Willison: Remote prompt injection in GitLab Duo leads to source code theft","https:\u002F\u002Fsimonwillison.net\u002F2025\u002FMay\u002F23\u002Fremote-prompt-injection-in-gitlab-duo\u002F","\u002Fimages\u002Fblog\u002Fllm-output-guardrails-moderation\u002Fcover.webp","\u002Fimages\u002Fblog\u002Fllm-output-guardrails-moderation\u002Fog.jpg","ai-engineer",[74,75,76],"en","de","hu","LLM output guardrails: moderation, safe rendering and validation before anything acts","What to check after the model answers: safe Markdown rendering, schema checks before actions, moderation classifiers, streaming rails and groundedness.","LLM output guardrails: water from a tap runs through a filter jug into a clean glass, pebbles caught at the top.",{"slug":81,"published":6,"minutes":82,"category":8,"tags":83,"tagPages":87,"keywords":88,"about":100,"sources":108,"cover":145,"og":146,"expertise":72,"locales":147,"lang":74,"title":148,"description":149,"coverAlt":150},"ai-red-teaming-checklist-llm-apps",12,[84,10,13,85,86],"AI red teaming","promptfoo","Penetration testing",[16],[89,90,91,92,93,94,95,96,97,98,99],"ai red teaming checklist","llm red teaming","red teaming llm applications","owasp genai red teaming guide","promptfoo red team","garak llm scanner","pyrit red teaming","llm penetration testing","owasp top 10 llm 2025 testing","jailbreak testing llm app","red team rag chatbot",[101,104,107],{"name":102,"url":103},"Red team","https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FRed_team",{"name":105,"url":106},"Prompt injection","https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FPrompt_injection",{"name":13,"url":38},[109,112,115,118,121,124,127,130,133,136,139,142],{"title":110,"url":111},"OWASP GenAI Security Project: GenAI Red Teaming Guide (January 2025)","https:\u002F\u002Fgenai.owasp.org\u002Fresource\u002Fgenai-red-teaming-guide\u002F",{"title":113,"url":114},"OWASP GenAI Security Project: Top 10 for LLM Applications 2025","https:\u002F\u002Fgenai.owasp.org\u002Fllm-top-10\u002F",{"title":116,"url":117},"Bullwinkel et al. (Microsoft): Lessons From Red Teaming 100 Generative AI Products (2025)","https:\u002F\u002Farxiv.org\u002Fabs\u002F2501.07238",{"title":119,"url":120},"NIST AI 600-1: Generative Artificial Intelligence Profile (July 2024)","https:\u002F\u002Fnvlpubs.nist.gov\u002Fnistpubs\u002Fai\u002FNIST.AI.600-1.pdf",{"title":122,"url":123},"Promptfoo Docs: Red team quickstart","https:\u002F\u002Fwww.promptfoo.dev\u002Fdocs\u002Fred-team\u002Fquickstart\u002F",{"title":125,"url":126},"Promptfoo Docs: Red team configuration","https:\u002F\u002Fwww.promptfoo.dev\u002Fdocs\u002Fred-team\u002Fconfiguration\u002F",{"title":128,"url":129},"Promptfoo Docs: Red team plugins","https:\u002F\u002Fwww.promptfoo.dev\u002Fdocs\u002Fred-team\u002Fplugins\u002F",{"title":131,"url":132},"Promptfoo Docs: Red team strategies","https:\u002F\u002Fwww.promptfoo.dev\u002Fdocs\u002Fred-team\u002Fstrategies\u002F",{"title":134,"url":135},"NVIDIA garak: LLM vulnerability scanner (GitHub)","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fgarak",{"title":137,"url":138},"Microsoft PyRIT documentation","https:\u002F\u002Fmicrosoft.github.io\u002FPyRIT\u002F",{"title":140,"url":141},"EU AI Act, Article 55: Obligations for providers of GPAI models with systemic risk","https:\u002F\u002Fartificialintelligenceact.eu\u002Farticle\u002F55\u002F",{"title":143,"url":144},"OWASP GenAI LLM Top 10 2026: final entries (GitHub)","https:\u002F\u002Fgithub.com\u002FGenAI-Security-Project\u002FGenAI-LLM-Top10\u002Ftree\u002Fmain\u002F2026\u002Ffinal","\u002Fimages\u002Fblog\u002Fai-red-teaming-checklist-llm-apps\u002Fcover.webp","\u002Fimages\u002Fblog\u002Fai-red-teaming-checklist-llm-apps\u002Fog.jpg",[74,75,76],"AI red teaming checklist for LLM apps: what to attack before your users do","A practical red teaming checklist for LLM features: scope, OWASP 2025 test cases, promptfoo, garak and PyRIT, human testers and regression tests.","LLM app red teaming: a person in a helmet with a checklist stands before a castle gate, a battering ram nearby.",{"slug":152,"published":153,"minutes":154,"category":155,"tags":156,"tagPages":161,"keywords":162,"about":173,"sources":182,"cover":201,"og":202,"expertise":72,"locales":203,"lang":74,"title":204,"description":205,"coverAlt":206},"text-to-sql-llm-guardrails","2026-10-16",8,"rag",[157,10,158,159,160],"Text-to-SQL","PostgreSQL","Agents","Analytics",[16],[163,164,165,166,167,168,169,170,171,172],"text to sql llm","text-to-sql guardrails","llm sql agent security","natural language to sql production","read only database role llm","bird benchmark text to sql","spider 2.0 benchmark","sqlglot validate sql","row level security llm","chat with your database",[174,177,180],{"name":175,"url":176},"SQL","https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FSQL",{"name":178,"url":179},"Natural language interface to 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door.",{"slug":208,"published":153,"minutes":209,"category":210,"tags":211,"tagPages":215,"keywords":217,"about":230,"sources":238,"cover":272,"og":273,"expertise":274,"locales":275,"lang":74,"title":276,"description":277,"coverAlt":278},"llm-endpoint-abuse-denial-of-wallet",14,"web",[212,10,213,13,214],"Nuxt","Rate limiting","Cost control",[216,16],"nuxt",[218,219,220,221,222,223,224,225,226,227,228,229],"denial of wallet llm","owasp llm10 unbounded consumption","rate limit llm api nuxt","nuxt security rate limiter","protect openai api key frontend","llm token budget per user","limit llm cost per user","nitro api rate limiting","cloudflare turnstile nuxt","anthropic spend limit","openai hard spend limit","llm prompt size limit",[231,233,236],{"name":213,"url":232},"https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FRate_limiting",{"name":234,"url":235},"Denial-of-service attack","https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FDenial-of-service_attack",{"name":212,"url":237},"https:\u002F\u002Fnuxt.com\u002F",[239,242,245,248,251,254,257,260,263,266,269],{"title":240,"url":241},"OWASP GenAI Security Project: LLM10:2025 Unbounded Consumption","https:\u002F\u002Fgenai.owasp.org\u002Fllmrisk\u002Fllm102025-unbounded-consumption\u002F",{"title":243,"url":244},"Nuxt Security: Rate Limiter middleware","https:\u002F\u002Fnuxt-security.vercel.app\u002Fmiddleware\u002Frate-limiter",{"title":246,"url":247},"Nuxt Security: Request Size Limiter middleware","https:\u002F\u002Fnuxt-security.vercel.app\u002Fmiddleware\u002Frequest-size-limiter",{"title":249,"url":250},"nuxt-auth-utils: README (GitHub)","https:\u002F\u002Fgithub.com\u002Fatinux\u002Fnuxt-auth-utils",{"title":252,"url":253},"h3: request utilities (getRequestIP, readValidatedBody)","https:\u002F\u002Fh3.dev\u002Futils\u002Frequest",{"title":255,"url":256},"Upstash: Ratelimiting algorithms","https:\u002F\u002Fupstash.com\u002Fdocs\u002Fredis\u002Fsdks\u002Fratelimit-ts\u002Falgorithms",{"title":258,"url":259},"Cloudflare Turnstile: Validate the token","https:\u002F\u002Fdevelopers.cloudflare.com\u002Fturnstile\u002Fget-started\u002Fserver-side-validation\u002F",{"title":261,"url":262},"Claude Platform Docs: Rate limits and spend limits","https:\u002F\u002Fplatform.claude.com\u002Fdocs\u002Fen\u002Fapi\u002Frate-limits",{"title":264,"url":265},"Claude Platform Docs: Token counting","https:\u002F\u002Fplatform.claude.com\u002Fdocs\u002Fen\u002Fbuild-with-claude\u002Ftoken-counting",{"title":267,"url":268},"OpenAI API Docs: Spend limits","https:\u002F\u002Fdevelopers.openai.com\u002Fapi\u002Fdocs\u002Fguides\u002Fspend-limits",{"title":270,"url":271},"OpenAI API Docs: Rate limits","https:\u002F\u002Fplatform.openai.com\u002Fdocs\u002Fguides\u002Frate-limits","\u002Fimages\u002Fblog\u002Fllm-endpoint-abuse-denial-of-wallet\u002Fcover.webp","\u002Fimages\u002Fblog\u002Fllm-endpoint-abuse-denial-of-wallet\u002Fog.jpg","vue-nuxt-developer",[74,75,76],"Denial of wallet: protecting public LLM endpoints in a Nuxt app","How to stop abuse and runaway cost on a public LLM route in Nuxt: auth, per-user rate limits, prompt caps, token budgets, Turnstile and spend limits.","Denial of wallet on LLM endpoints: a turnstile slows a queue of tiny robots heading for an open wallet.",{"slug":280,"published":281,"minutes":82,"category":8,"tags":282,"tagPages":287,"keywords":289,"about":298,"sources":311,"cover":356,"og":357,"expertise":72,"locales":358,"lang":74,"title":359,"description":360,"coverAlt":361},"dpia-llm-feature-worked-example","2026-10-01",[283,284,10,285,286],"DPIA","GDPR","Data protection","AI Act",[288,16],"gdpr",[290,291,292,293,294,295,296,297],"DPIA for 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EUR-Lex",{"title":315,"url":304},"WP29 guidelines on DPIA, WP248 rev.01 (European Commission item page)",{"title":317,"url":318},"WP248 rev.01 PDF, adopted 4 April 2017 and revised 4 October 2017","https:\u002F\u002Fec.europa.eu\u002Fnewsroom\u002Fjust\u002Fdocument.cfm?doc_id=47711",{"title":320,"url":321},"EDPB Guidelines 07\u002F2020 on the concepts of controller and processor","https:\u002F\u002Fwww.edpb.europa.eu\u002Fsystem\u002Ffiles\u002F2023-10\u002Fedpb_guidelines_202007_controllerprocessor_final_en.pdf",{"title":323,"url":324},"EDPB Opinion 28\u002F2024 on AI models, adopted 17 December 2024","https:\u002F\u002Fwww.edpb.europa.eu\u002Fsystem\u002Ffiles\u002F2024-12\u002Fedpb_opinion_202428_ai-models_en.pdf",{"title":326,"url":327},"EDPB news release on Opinion 28\u002F2024","https:\u002F\u002Fwww.edpb.europa.eu\u002Fnews\u002Fedpb-opinion-on-ai-models-gdpr-principles-support-responsible-ai_en",{"title":329,"url":330},"EDPB, Report of the work undertaken by the ChatGPT Taskforce, 23 May 2024","https:\u002F\u002Fwww.edpb.europa.eu\u002Fsystem\u002Ffiles\u002F2024-05\u002Fedpb_20240523_report_chatgpt_taskforce_en.pdf",{"title":332,"url":333},"DSFA-V, BGBl. II Nr. 278\u002F2018 (RIS)","https:\u002F\u002Fwww.ris.bka.gv.at\u002Feli\u002Fbgbl\u002FII\u002F2018\u002F278",{"title":335,"url":336},"DSFA-AV, BGBl. II Nr. 108\u002F2018 (RIS)","https:\u002F\u002Fwww.ris.bka.gv.at\u002Feli\u002Fbgbl\u002FII\u002F2018\u002F108",{"title":338,"url":307},"OWASP Top 10 for LLM Applications 2025: LLM01 Prompt Injection",{"title":340,"url":341},"OWASP Top 10 for LLM Applications 2025: LLM02 Sensitive Information Disclosure","https:\u002F\u002Fgenai.owasp.org\u002Fllmrisk\u002Fllm022025-sensitive-information-disclosure\u002F",{"title":343,"url":344},"OpenAI, Data controls in the OpenAI platform","https:\u002F\u002Fdevelopers.openai.com\u002Fapi\u002Fdocs\u002Fguides\u002Fyour-data",{"title":346,"url":347},"Commission Implementing Decision (EU) 2023\u002F1795 on the EU–US Data Privacy Framework","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdec_impl\u002F2023\u002F1795\u002Foj\u002Feng",{"title":349,"url":350},"CJEU, Case C-184\u002F20, OT v Vyriausioji tarnybinės etikos komisija","https:\u002F\u002Feur-lex.europa.eu\u002Flegal-content\u002FEN\u002FTXT\u002F?uri=CELEX:62020CJ0184",{"title":352,"url":310},"Regulation (EU) 2024\u002F1689 (AI Act), EUR-Lex",{"title":354,"url":355},"Regulation (EU) 2026\u002F1744 (Digital Omnibus on AI), EUR-Lex","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2026\u002F1744\u002Foj","\u002Fimages\u002Fblog\u002Fdpia-llm-feature-worked-example\u002Fcover.webp","\u002Fimages\u002Fblog\u002Fdpia-llm-feature-worked-example\u002Fog.jpg",[74,75,76],"DPIA for an LLM support assistant: a worked example under GDPR Art. 35","A worked DPIA under GDPR Art. 35 for an AI assistant that drafts customer email replies from order data: when it is needed, the risks and owners.","DPIA for an LLM support assistant: a clipboard form next to a robot with a speech bubble, a magnifier and a stamp.",{"slug":363,"published":364,"minutes":365,"category":8,"tags":366,"tagPages":367,"keywords":368,"about":377,"sources":382,"cover":407,"og":408,"expertise":72,"locales":409,"lang":74,"title":410,"description":411,"coverAlt":412},"lakera-guard","2026-08-04",9,[105,11,10,12],[17,16],[369,370,371,372,373,374,375,376],"lakera guard","lakera guard review","prompt injection filter","prompt injection detection","llm guardrails comparison","pint benchmark","check point ai guardrails","lakera pricing",[378,379],{"name":105,"url":106},{"name":380,"url":381},"Check Point","https:\u002F\u002Fwww.checkpoint.com\u002F",[383,386,389,392,395,398,401,404],{"title":384,"url":385},"Lakera documentation: Guard API","https:\u002F\u002Fdocs.lakera.ai\u002Fdocs\u002Fapi\u002Fguard",{"title":387,"url":388},"Guard API endpoint reference","https:\u002F\u002Fdocs.lakera.ai\u002Fapi-reference\u002Flakera-api\u002Fguard\u002Fscreen-content",{"title":390,"url":391},"Lakera documentation: projects","https:\u002F\u002Fdocs.lakera.ai\u002Fdocs\u002Fprojects",{"title":393,"url":394},"Lakera documentation: self-hosting","https:\u002F\u002Fdocs.lakera.ai\u002Fdocs\u002Fselfhosting",{"title":396,"url":397},"Lakera platform pricing","https:\u002F\u002Fplatform.lakera.ai\u002Fpricing",{"title":399,"url":400},"PINT benchmark on GitHub","https:\u002F\u002Fgithub.com\u002Flakeraai\u002Fpint-benchmark",{"title":402,"url":403},"Lakera homepage","https:\u002F\u002Fwww.lakera.ai\u002F",{"title":405,"url":406},"Check Point press release on the Lakera acquisition","https:\u002F\u002Fwww.checkpoint.com\u002Fpress-releases\u002Fcheck-point-acquires-lakera-to-deliver-end-to-end-ai-security-for-enterprises\u002F","\u002Fimages\u002Fblog\u002Flakera-guard\u002Fcover.webp","\u002Fimages\u002Fblog\u002Flakera-guard\u002Fog.jpg",[74,75,76],"Lakera Guard: prompt injection filtering at the request boundary","A review of Lakera Guard: one endpoint before the model, the PINT benchmark behind its scores, and why the free tier stops at 10,000 requests a month.","Lakera Guard prompt injection filter: a guard at a doorway holds a sieve that catches one envelope with a hook.",{"slug":414,"published":415,"updated":416,"minutes":82,"category":8,"tags":417,"tagPages":421,"keywords":422,"about":433,"sources":442,"cover":503,"og":504,"expertise":72,"locales":505,"lang":74,"title":506,"description":507,"coverAlt":508},"pii-redaction-llm-pipelines","2026-06-26","2026-09-01",[418,284,419,10,420],"PII redaction","Microsoft Presidio","Pseudonymisation",[288,16],[423,424,425,426,427,428,429,430,431,432],"PII redaction LLM","how to remove PII before sending to LLM","Microsoft Presidio tutorial","PII detection German Hungarian","pseudonymisation vs anonymisation GDPR","reversible tokenization LLM prompts","redact PII in logs and traces","LLM data masking","PII guardrail LiteLLM","test PII detection recall",[434,437,439],{"name":435,"url":436},"Personal data","https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FPersonal_data",{"name":300,"url":438},"https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FGeneral_Data_Protection_Regulation",{"name":440,"url":441},"Data anonymization","https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FData_anonymization",[443,446,449,452,455,458,461,464,467,470,473,476,479,482,485,488,491,494,497,500],{"title":444,"url":445},"Microsoft Presidio: documentation (limitations, methods)","https:\u002F\u002Fpresidio.dataprivacystack.org\u002F",{"title":447,"url":448},"Presidio: supported entities and country-specific recognizers","https:\u002F\u002Fpresidio.dataprivacystack.org\u002Fsupported_entities\u002F",{"title":450,"url":451},"Presidio: supporting additional languages","https:\u002F\u002Fpresidio.dataprivacystack.org\u002Fanalyzer\u002Flanguages\u002F",{"title":453,"url":454},"Presidio: anonymizer operators","https:\u002F\u002Fpresidio.dataprivacystack.org\u002Fanonymizer\u002F",{"title":456,"url":457},"Google Cloud: infoTypes reference","https:\u002F\u002Fdocs.cloud.google.com\u002Fsensitive-data-protection\u002Fdocs\u002Finfotypes-reference",{"title":459,"url":460},"Google Cloud: pseudonymization in Sensitive Data Protection","https:\u002F\u002Fdocs.cloud.google.com\u002Fsensitive-data-protection\u002Fdocs\u002Fpseudonymization",{"title":462,"url":463},"Microsoft Learn: Azure Language PII detection language support","https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fazure\u002Fai-services\u002Flanguage-service\u002Fpersonally-identifiable-information\u002Flanguage-support",{"title":465,"url":466},"AWS: Detecting PII entities with Amazon Comprehend","https:\u002F\u002Fdocs.aws.amazon.com\u002Fcomprehend\u002Flatest\u002Fdg\u002Fhow-pii.html",{"title":468,"url":469},"spaCy: models and languages","https:\u002F\u002Fspacy.io\u002Fusage\u002Fmodels",{"title":471,"url":472},"Hugging Face: novakat\u002Fnerkor-hubert (Hungarian NER)","https:\u002F\u002Fhuggingface.co\u002Fnovakat\u002Fnerkor-hubert",{"title":474,"url":475},"arXiv: An Evaluation Study of Hybrid Methods for Multilingual PII Detection","https:\u002F\u002Farxiv.org\u002Fabs\u002F2510.07551",{"title":477,"url":478},"LiteLLM: Presidio PII masking guardrail","https:\u002F\u002Fdocs.litellm.ai\u002Fdocs\u002Fproxy\u002Fguardrails\u002Fpii_masking_v2",{"title":480,"url":481},"Langfuse: masking","https:\u002F\u002Flangfuse.com\u002Fdocs\u002Fobservability\u002Ffeatures\u002Fmasking",{"title":483,"url":484},"GDPR Article 4: definitions (pseudonymisation, 4(5))","https:\u002F\u002Fgdpr-info.eu\u002Fart-4-gdpr\u002F",{"title":486,"url":487},"EDPB: Guidelines 01\u002F2025 on Pseudonymisation","https:\u002F\u002Fwww.edpb.europa.eu\u002Four-work-tools\u002Fdocuments\u002Fpublic-consultations\u002F2025\u002Fguidelines-012025-pseudonymisation_en",{"title":489,"url":490},"IAPP: EDPB publishes draft guidelines on pseudonymization","https:\u002F\u002Fiapp.org\u002Fnews\u002Fa\u002F-what-s-in-a-name-edpb-publishes-draft-guidelines-on-pseudonymization",{"title":492,"url":493},"Taylor Wessing: Analysis of the CJEU judgment in C-413\u002F23 P (EDPS v SRB)","https:\u002F\u002Fwww.taylorwessing.com\u002Fen\u002Finsights-and-events\u002Finsights\u002F2025\u002F09\u002Fanalysis-of-the-cjeu-judgment",{"title":495,"url":496},"Jones Day: CJEU clarifies scope of personal data in EDPS v SRB","https:\u002F\u002Fwww.jonesday.com\u002Fen\u002Finsights\u002F2025\u002F09\u002Fcjeu-clarifies-scope-of-personal-data-in-edps-v-srb-decision",{"title":498,"url":499},"IAPP: leaked Council Digital Omnibus compromise drops the revised personal data definition","https:\u002F\u002Fiapp.org\u002Fnews\u002Fa\u002Feu-member-states-leaked-digital-omnibus-compromise-proposal-eliminates-revised-gdpr-definition-of-personal-data",{"title":501,"url":502},"Law Health Tech: Pseudonymisation under the GDPR and the Digital Omnibus (May 2026)","https:\u002F\u002Flawhealthtech.com\u002F2026\u002F05\u002F04\u002Fpseudonymisation-under-the-gdpr-where-we-are-what-may-change-under-the-digital-omnibus-and-what-regulators-think\u002F","\u002Fimages\u002Fblog\u002Fpii-redaction-llm-pipelines\u002Fcover.webp","\u002Fimages\u002Fblog\u002Fpii-redaction-llm-pipelines\u002Fog.jpg",[74,75,76],"PII redaction in LLM pipelines: where to redact, how, and what GDPR says","Where to redact PII in LLM pipelines: reversible tokens vs masking, Presidio and cloud DLP, German and Hungarian gaps, GDPR for pseudonymised data.","PII redaction in LLM pipelines: a hand blacks out lines on a page with a marker while a robot waits for it.",{"slug":510,"published":511,"updated":512,"minutes":365,"category":8,"tags":513,"tagPages":515,"keywords":516,"about":521,"sources":528,"cover":540,"og":541,"expertise":72,"locales":542,"lang":74,"title":543,"description":544,"coverAlt":545},"rebuff","2026-06-22","2026-07-09",[105,10,11,514],"Canary tokens",[16,17],[510,372,517,518,519,520],"rebuff python sdk","llm prompt injection guardrail","canary token leak detection","rebuff alternative",[522,525],{"name":523,"url":524},"Rebuff","https:\u002F\u002Fgithub.com\u002Fprotectai\u002Frebuff",{"name":526,"url":527},"Large language model","https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FLarge_language_model",[529,531,534,537],{"title":530,"url":524},"Rebuff repository, archived 16 May 2025",{"title":532,"url":533},"Rebuff 0.1.1 on PyPI, released 20 January 2024","https:\u002F\u002Fpypi.org\u002Fproject\u002Frebuff\u002F",{"title":535,"url":536},"LangChain: Rebuff, detecting prompt injection attacks","https:\u002F\u002Fwww.langchain.com\u002Fblog\u002Frebuff",{"title":538,"url":539},"LLM Guard repository, archived 9 July 2026","https:\u002F\u002Fgithub.com\u002Fprotectai\u002Fllm-guard","\u002Fimages\u002Fblog\u002Frebuff\u002Fcover.webp","\u002Fimages\u002Fblog\u002Frebuff\u002Fog.jpg",[74,75,76],"Rebuff: four layers of prompt injection detection, now archived","Rebuff scores prompts with heuristics, an LLM, a vector store of past attacks and canary tokens. Archived in May 2025; last release January 2024.","Rebuff prompt injection detection: a closed archive box sits before four layers of defence: moat, fence, wall and gate.",1793451237700]