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Anthropic’s Project Glasswing: Indian Entities Boost Cybersecurity With Mythos AI

by India News Online Team
June 6, 2026
in Business
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Anthropic’s Project Glasswing: Indian Entities Boost Cybersecurity With Mythos AI
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Indian government and private sector entities are now leveraging Anthropic’s cutting-edge Mythos AI model through Project Glasswing to bolster cybersecurity and detect critical software vulnerabilities, even as Anthropic warns about the rapid pace of AI development and its potential societal risks.

Key Points

  • Indian government and private sector organisations have secured access to Anthropic’s Mythos AI model via Project Glasswing.
  • Project Glasswing is a cybersecurity initiative using advanced AI to identify software vulnerabilities in critical infrastructure.
  • The programme has expanded globally, now including 150 additional organisations across 15+ countries, targeting sectors like power, water, and healthcare.
  • Anthropic has also urged AI labs to consider slowing down AI development due to concerns about systems accelerating their own progress beyond human oversight, posing societal risks.

Government agencies and private sector firms are among a select group of Indian organisations that have secured access to Anthropic’s Mythos artificial intelligence model as part of the recent expansion of Project Glasswing, according to sources familiar with the matter.

Asked about the number of Indian entities that have got access to the model, sources said the figure is in the single digit for now. An email sent to Anthropic did not elicit an immediate response. Sources indicated that participating Indian entities span both government and private sectors, but did not disclose specific names.

 

Anthropic’s Project Glasswing Expands Globally

Described as a “collaborative effort to secure the world’s most important software”, Project Glasswing is Anthropic’s initiative aimed at strengthening cybersecurity by giving select organisations access to Claude Mythos Preview, an advanced AI model that can identify software vulnerabilities.

When the programme was announced globally in April, about 50 partners were granted access to the model initially, and Anthropic said they had since uncovered more than 10,000 high- or critical-severity security flaws across codebases.

Earlier this week, Anthropic announced a major expansion of Project Glasswing, widening the ambit to about 150 additional organisations across more than 15 countries. The new cohort includes operators of critical infrastructure in sectors including power, water, healthcare, communications and hardware.

“And many of the new partners are vendors – companies or non-profits that maintain codebases that are relied upon by lots of other organisations around the world, including governments,” the company said in a statement on June 2.

Anthropic said partner organisations are those for which a successful cyberattack could have far-reaching ramifications, potentially affecting more than 100 million people in some cases. Put simply, the access is expected to enable participating organisations to detect security vulnerabilities in digital infrastructure, test defences and accelerate patching of vulnerable software systems.

AI Development Pace And Societal Risks

Meanwhile, in its latest blog, Anthropic has urged leading artificial intelligence labs to consider moderating the pace of AI development, warning that increasingly capable systems could soon acquire the ability to accelerate their own progress in ways that outstrip human oversight and create broader societal risks.

“We believe it would be good for the world to have the option to slow or temporarily pause frontier AI development to enable societal structures and alignment research to keep up with the advance of the technology,” the company said in the blogpost titled ‘When AI builds itself’, as it outlined the speed at which advanced AI models are evolving.

Disclaimer: News content is sourced from the stated source. Headlines, summaries, section headers, and images are automatically generated or selected using AI/algorithms and may not always be fully accurate. Readers are advised to refer to the full article for complete context.



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