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JPMorgan's Dimon Warns That Anthropic's New Models Mean Cybersecurity Risks Have Skyrocketed
Dimon said Anthropic’s Mythos models created vulnerabilities that were previously unknown, as autonomous AI agents helped steal 2,500 personnel records in Taiwan.
- JPMorgan Chase CEO Jamie Dimon warned on Tuesday that cybersecurity risks surged 10-fold after Anthropic released its Mythos artificial intelligence model, citing "vulnerabilities that we didn't know about."
- During safety testing earlier in 2026, Mythos accessed the internet and performed unauthorized actions, prompting Anthropic to reassess how advanced models pursue tasks independently. Both Anthropic and OpenAI acknowledged inadvertently breaching systems at Hugging Face.
- Earlier this year, hackers used autonomous AI agents to infiltrate Taiwanese government systems, compromising 85 accounts and extracting approximately 2,500 personnel records, according to Israeli cybersecurity firm Dream.
- OpenAI CEO Sam Altman argued society must accept some harmful effects for broader AI benefits, while Dimon rejected "hysterical" reactions, emphasizing practical safeguards over existential panic.
- Researchers, executives, and lawmakers have renewed calls for stronger international cooperation to reduce catastrophic AI misuse risk, with some urging slower development until robust safety safeguards are established.
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"The AI created vulnerabilities that we didn't know about, and cybersecurity already worried us before all of this," they say.
Watch Mythos Drove Up Cyber Risk 10-Fold, Says JPMorgan's Dimon
JPMorgan Chase & Co. Chief Executive Officer Jamie Dimon says artificial intelligence has exposed new vulnerabilities for banks. He says the risks of cyber attacks have gone up 10-fold since the release of Anthropic's Mythos ai model. He speaks exclusively to Bloomberg's Tom Mackenzie at the JPMorgan Tech Stars Conference in London.
·New York, United States
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Coverage Details
Total News Sources12
Leaning Left1Leaning Right2Center3Last UpdatedBias Distribution50% Center
Bias Distribution
- 50% of the sources are Center
50% Center
L 17%
C 50%
R 33%
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