DARPA\u2019s AI Cyber Challenge reveals winning models for automated vulnerability discovery and patching | CyberScoop<\/title> <meta name=\"description\" content=\"The initiative seeks to patch vulnerabilities in open-source code before they are exploited by would-be attackers. Now comes the hard part \u2014 putting the systems to the test in the real world.\"> <link rel=\"canonical\" href=\"https:\/\/cyberscoop.com\/darpa-ai-cyber-challenge-winners-def-con-2025\/\"> <meta property=\"og:locale\" content=\"en_US\"> <meta property=\"og:type\" content=\"article\"> <meta property=\"og:title\" content=\"DARPA\u2019s AI Cyber Challenge reveals winning models for automated vulnerability discovery and patching\"> <meta property=\"og:description\" content=\"The initiative seeks to patch vulnerabilities in open-source code before they are exploited by would-be attackers. Now comes the hard part \u2014 putting the systems to the test in the real world.\"> <meta property=\"og:url\" content=\"https:\/\/cyberscoop.com\/darpa-ai-cyber-challenge-winners-def-con-2025\/\"> <meta property=\"og:site_name\" content=\"CyberScoop\"> <meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/cyberscoop\/\"> <meta property=\"article:published_time\" content=\"2025-08-08T21:53:16+00:00\"> <meta property=\"article:modified_time\" content=\"2025-08-08T21:53:19+00:00\"> <meta property=\"og:image\" content=\"https:\/\/ddi.mohflo.net\/wp-content\/uploads\/2025\/08\/darpas-ai-cyber-challenge-reveals-winning-models-for-automated-vulnerability-discovery-and-patching-2.jpg\"> <meta property=\"og:image:width\" content=\"2015\"> <meta property=\"og:image:height\" content=\"1488\"> <meta property=\"og:image:type\" content=\"image\/jpeg\"> <meta name=\"author\" content=\"Matt Kapko\"> <meta name=\"twitter:card\" content=\"summary_large_image\"> <meta 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class=\"visually-hidden\">Close<\/span> <\/button> <\/section>\n<article class=\"single-article content\">\n<div class=\"single-article__container js-single-article-content\">\n<header class=\"single-article__header \" readability=\"25.572886297376\">\n<div class=\"single-article__header-content\" readability=\"31.792682926829\">\n<p> The initiative seeks to patch vulnerabilities in open-source code before they are exploited by would-be attackers. Now comes the hard part \u2014 putting the systems to the test in the real world. <\/p>\n<p>   <\/div>\n<div class=\"single-article__cover-wrap\">\n<figure class=\"single-article__cover\"> <img data-recalc-dims=\"1\" fetchpriority=\"high\" width=\"640\" height=\"473\" src=\"https:\/\/i0.wp.com\/ddi.mohflo.net\/wp-content\/uploads\/2025\/08\/darpas-ai-cyber-challenge-reveals-winning-models-for-automated-vulnerability-discovery-and-patching.jpg?resize=640%2C473&ssl=1\" class=\"single-article__cover-image wp-post-image\" alt decoding=\"async\" fetchpriority=\"high\" srcset=\"https:\/\/ddi.mohflo.net\/wp-content\/uploads\/2025\/08\/darpas-ai-cyber-challenge-reveals-winning-models-for-automated-vulnerability-discovery-and-patching-2.jpg 2015w, https:\/\/ddi.mohflo.net\/wp-content\/uploads\/2025\/08\/darpas-ai-cyber-challenge-reveals-winning-models-for-automated-vulnerability-discovery-and-patching-2.jpg?resize=300,222 300w, https:\/\/ddi.mohflo.net\/wp-content\/uploads\/2025\/08\/darpas-ai-cyber-challenge-reveals-winning-models-for-automated-vulnerability-discovery-and-patching-2.jpg?resize=768,567 768w, https:\/\/ddi.mohflo.net\/wp-content\/uploads\/2025\/08\/darpas-ai-cyber-challenge-reveals-winning-models-for-automated-vulnerability-discovery-and-patching-2.jpg?resize=1024,756 1024w, https:\/\/ddi.mohflo.net\/wp-content\/uploads\/2025\/08\/darpas-ai-cyber-challenge-reveals-winning-models-for-automated-vulnerability-discovery-and-patching-2.jpg?resize=1536,1134 1536w, https:\/\/ddi.mohflo.net\/wp-content\/uploads\/2025\/08\/darpas-ai-cyber-challenge-reveals-winning-models-for-automated-vulnerability-discovery-and-patching-2.jpg?resize=600,443 600w, https:\/\/ddi.mohflo.net\/wp-content\/uploads\/2025\/08\/darpas-ai-cyber-challenge-reveals-winning-models-for-automated-vulnerability-discovery-and-patching-2.jpg?resize=228,168 228w, https:\/\/ddi.mohflo.net\/wp-content\/uploads\/2025\/08\/darpas-ai-cyber-challenge-reveals-winning-models-for-automated-vulnerability-discovery-and-patching-2.jpg?resize=456,337 456w, https:\/\/ddi.mohflo.net\/wp-content\/uploads\/2025\/08\/darpas-ai-cyber-challenge-reveals-winning-models-for-automated-vulnerability-discovery-and-patching-2.jpg?resize=914,675 914w, https:\/\/ddi.mohflo.net\/wp-content\/uploads\/2025\/08\/darpas-ai-cyber-challenge-reveals-winning-models-for-automated-vulnerability-discovery-and-patching-2.jpg?resize=1142,843 1142w\" sizes=\"(max-width: 914px) 100vw, 914px\"><figcaption> (Getty Images) <\/figcaption><\/figure>\n<\/p><\/div>\n<\/header>\n<div class=\"single-article__content\">\n<div class=\"single-article__content-inner has-drop-cap\"> <html readability=\"57.826480122846\"><body readability=\"118.73810422961\"><\/p>\n<p>The Pentagon\u2019s two-year public competition to spur the development of cyber-reasoning systems that use large language models to autonomously find and patch vulnerabilities in open-source software concluded Friday with $8.5 awarded to three teams of security specialists at DEF CON. <\/p>\n<p>The Defense Advanced Research Project Agency\u2019s AI Cyber Challenge seeks to address a persistent bottleneck in cybersecurity \u2014 patching vulnerabilities before they are discovered or exploited by would-be attackers. <\/p>\n<p>\u201cWe\u2019re living in a world right now that has ancient digital scaffolding that\u2019s holding everything up,\u201d DARPA Director Stephen Winchell said. \u201cA lot of the code bases, a lot of the languages, a lot of the ways we do business, and everything we\u2019ve built on top of it has all incurred huge technical debt\u2026 It is a problem that is beyond human scale.\u201d <\/p>\n<p>The seven semifinalists that earned their spot out of <a href=\"https:\/\/cyberscoop.com\/darpa-competition-shows-promise-of-using-ai-to-find-and-patch-bugs\/\">90 teams convened at last year\u2019s DEF CON<\/a> were scored against their models\u2019 ability to quickly, accurately and successfully identify and generate patches for synthetic vulnerabilities across 54 million lines of code. The models discovered 77% of the vulnerabilities presented in the final scoring round and patched 61% of those synthetic defects at an average speed of 45 minutes, the competition organizers said.<\/p>\n<div class=\"ad ad--inline_1 \">\n<div class=\"ad__inner\"> <span class=\"screen-reader-text\">Advertisement<\/span> <\/div>\n<\/div>\n<p>The models also discovered 18 real zero-day vulnerabilities, including six in the C programming language and 12 in Java codebases. The teams\u2019 models patched none of the C codebase zero-days, but automatically patched 11 of the Java zero-days, according to the final results shared Friday.<\/p>\n<p>Team Atlanta took the first-place prize of $4 million, Trail of Bits won second place and $3 million in prize money, and Theori ranked third, taking home $1.5 million. The competition\u2019s organizers allocated an additional $1.4 million in prize money for participants who can demonstrate when their technology is deployed into critical infrastructure. <\/p>\n<p>Representatives from the three winning teams said they plan to reinvest the majority of the prize money back into research and further development of their cyber-reasoning systems or explore ways to commercialize the technology.<\/p>\n<p>Four of the models developed under the competition were made available as open source Friday, and the three remaining models will be released in the coming weeks, officials said.<\/p>\n<p>\u201cOur hope is this technology will harden source code by being integrated during the development stage, the most critical point in the software lifecycle,\u201d Andrew Carney, program manager of the competition, said during a media briefing about the challenge last week. <\/p>\n<div class=\"ad ad--inline_1 \">\n<div class=\"ad__inner\"> <span class=\"screen-reader-text\">Advertisement<\/span> <\/div>\n<\/div>\n<p>Open sourcing the cyber-reasoning systems and the AI Cyber Challenge\u2019s infrastructure should also allow others to experiment and improve upon what the competition helped foster, he said. DARPA and partners across government and the private sector involved in the program are pursuing paths to push the technology developed during the competition into open-source software communities and commercial vendors for broader adoption.<\/p>\n<p>DARPA\u2019s AI Cyber Challenge is a public-private endeavor, with Google, Microsoft, Anthropic and OpenAI each donating $350,000 in LLM credits and additional support. The initiative seeks to <a href=\"https:\/\/cyberscoop.com\/darpa-ai-grand-challenge-rsac-2025-patching\/\">test AI\u2019s ability to identify and patch vulnerabilities<\/a> in open-source code of vital importance throughout critical infrastructure, including health care. <\/p>\n<p>Jim O\u2019Neill, deputy secretary of the Department of Health and Human Services, spoke to the importance of this work during the AI Cyber Challenge presentation at DEF CON. \u201cHealth systems are among the hardest networks to secure. Unlike other industries, hospitals must maintain 24\/7 uptime, and they don\u2019t get to reboot. They rely on highly specialized, legacy devices and complex IT ecosystems,\u201d he said. <\/p>\n<p>\u201cAs a result, patching a vulnerability in health care can take an average of 491 days, compared to 60 to 90 days in most other industries,\u201d O\u2019Neill added. \u201cMany cybersecurity products, unfortunately, are security theater. We need assertive proof-of-work approaches to keep networks, hospitals and patients safer.\u201d<\/p>\n<p>Health officials and others directly involved in the AI Cyber Challenge acknowledged the problems posed by insecure software are vast, but said the results showcased from this effort provide a glimmer of hope. <\/p>\n<div class=\"ad ad--inline_1 \">\n<div class=\"ad__inner\"> <span class=\"screen-reader-text\">Advertisement<\/span> <\/div>\n<\/div>\n<p>\u201cThe magnitude of the problem is so incredibly overwhelming and unreasonable that this is starting to make it so that maybe we can actually secure networks \u2014 maybe,\u201d Jennifer Roberts, director of resilient systems at HHS\u2019s Advanced Research Projects Agency for Health, said during a media briefing at DEF CON after the winners were announced. <\/p>\n<p>Kathleen Fisher, director of DARPA\u2019s Information Innovation Office, shared a similar cautiously optimistic outlook. \u201cSoftware runs the world, and the software that is running the world is riddled with vulnerabilities,\u201d she said.<\/p>\n<p>\u201cWe have this sense of learned helplessness, that there\u2019s just nothing we can do about it. That\u2019s the way software is,\u201d she continued. \u201cThe AI Cyber Challenge \u201cpoints to a brighter future where software does what it\u2019s supposed to do and nothing else.\u201d<\/p>\n<p><\/body> <\/p>\n<footer class=\"single-article__footer\" readability=\"3.2234042553191\">\n<div class=\"author-card\" readability=\"14\">\n<div class=\"author-card__avatar\">\n<figure class=\"author-card__image-wrap\"> <img data-recalc-dims=\"1\" decoding=\"async\" class=\"author-card__image\" src=\"https:\/\/i0.wp.com\/ddi.mohflo.net\/wp-content\/uploads\/2025\/08\/darpas-ai-cyber-challenge-reveals-winning-models-for-automated-vulnerability-discovery-and-patching-1.jpg?w=640&ssl=1\" alt=\"Matt Kapko\"> <\/figure>\n<\/p><\/div>\n<p><h4 class=\"author-card__name\">Written by Matt Kapko<\/h4>\n<p> Matt Kapko is a reporter at CyberScoop. His beat includes cybercrime, ransomware, software defects and vulnerability (mis)management. The lifelong Californian started his journalism career in 2001 with previous stops at Cybersecurity Dive, CIO, SDxCentral and RCR Wireless News. 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{"id":7880,"date":"2025-08-08T16:53:16","date_gmt":"2025-08-08T21:53:16","guid":{"rendered":"https:\/\/cyberscoop.com\/?p=85504"},"modified":"2025-08-08T16:53:16","modified_gmt":"2025-08-08T21:53:16","slug":"darpas-ai-cyber-challenge-reveals-winning-models-for-automated-vulnerability-discovery-and-patching","status":"publish","type":"post","link":"https:\/\/ddi.mohflo.net\/index.php\/2025\/08\/08\/darpas-ai-cyber-challenge-reveals-winning-models-for-automated-vulnerability-discovery-and-patching\/","title":{"rendered":"DARPA\u2019s AI Cyber Challenge reveals winning models for automated vulnerability discovery and patching"},"content":{"rendered":"