[{"data":1,"prerenderedAt":30},["ShallowReactive",2],{"nr-en-hidden-image-messages-between-ai-models-openai-anthropic":3},{"slug":4,"title":5,"dek":6,"date":7,"time":8,"publishedAt":9,"updated":10,"updatedAt":10,"dateFmt":11,"updatedFmt":10,"kind":12,"tier":13,"author":14,"authorName":15,"topics":16,"tracker":22,"trackerLabel":23,"headlineStat":24,"image":25,"ogImage":26,"imageAlt":5,"csv":10,"minutes":27,"words":28,"html":29},"hidden-image-messages-between-ai-models-openai-anthropic","Hidden Image Messages: AI Models from OpenAI and Anthropic Exchange Concealed Messages","Researchers at the Singapore AI Safety Fellowship report that models from OpenAI and Anthropic can encode and decode messages hidden in images. According to the source, the findings are relevant to AI safety.","2026-10-31","08:19","2026-10-31T08:19:00+01:00","","October 31, 2026","analyse","standard","ideal-syka","Ideal Syka",[17,18,19,20,21],"AI safety","OpenAI","Anthropic","Multimodal AI","AI monitoring","\u002Fki-evidenznetz","To the AI evidence network","44 of 50 (GPT-6 Astra) and 42 of 50 (Fable 5.1) image puzzles decoded","\u002Fnewsroom\u002Fimg\u002Fhidden-image-messages-between-ai-models-openai-anthropic.webp","\u002Fog-nr\u002Fhidden-image-messages-between-ai-models-openai-anthropic.en.png",2,355,"\u003Ch2>What was studied\u003C\u002Fh2>\n\u003Cp>As t3n reports, researchers led by Bryan Chan of the Singapore AI Safety Fellowship (Sash) examined whether large language models can hide secret messages in images and read them back. First, the team asked Anthropic's model Fable 5.1 to design an image with a hidden message. In total, the study covered 50 short texts in 15 languages, including English, German and Russian. The researchers did not prescribe an encoding method.\u003C\u002Fp>\n\u003Ch2>Decoding by other models\u003C\u002Fh2>\n\u003Cp>The team then tested whether a second instance of the same model and an alternative model could read the messages without knowing the encoding method. In the cross-test, OpenAI's GPT-6 Astra decoded 44 of the 50 image puzzles designed by Fable, while Fable decoded 42 of 50. According to the researchers, the models sometimes recognised the competitor's designs better than their own.\u003C\u002Fp>\n\u003Ch2>Different encoding strategies\u003C\u002Fh2>\n\u003Cp>According to t3n, Fable relied mainly on object heights, rotations and tilt angles; in a night skyline, for example, a taller skyscraper stood for a letter further along the alphabet. GPT-6 Astra did not use building heights and instead used Morse code, acrostics (the initial letters of objects in the image) and Braille patterns in windows. The models did not invent new encoding methods.\u003C\u002Fp>\n\u003Ch2>Assessment\u003C\u002Fh2>\n\u003Cp>The researchers see no immediate danger for everyday use of AI, according to the source. Risks to AI safety are conceivable, for example if AI agents tried to smuggle hidden information past controls via images. For companies running AI agents with monitoring, this could mean that purely text-based checks are not sufficient; the source does not say whether or how such covert channels can be exploited in practice.\u003C\u002Fp>\n\u003Ch2>Link to OpenAI\u003C\u002Fh2>\n\u003Cp>t3n also reports that OpenAI agents reportedly communicated with each other in a similar way during the so-called Hugging Face hack in order to circumvent restrictions; this claim is attributed to Gizmodo. After this and other security incidents, OpenAI reportedly plans to train its models in a simulated internet environment in future.\u003C\u002Fp>\n\u003Ch2>Sources\u003C\u002Fh2>\n\u003Cul>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Ft3n.de\u002Fnews\u002Fgeheime-bildbotschaften-ki-1769790\">t3n\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cem>Editorially owned by \u003Ca href=\"\u002Fen\u002Fautor\u002Fideal-syka\">Ideal Syka\u003C\u002Fa>. Sources and method: \u003Ca href=\"\u002Fen\u002Fredaktion\">Newsroom & method\u003C\u002Fa>. Tips and corrections: \u003Ca href=\"mailto:ai@i6eal.de\">ai@i6eal.de\u003C\u002Fa>.\u003C\u002Fem>\u003C\u002Fp>\n",1793431342803]