GoKawiilA new study suggests that while AI is rapidly accelerating vulnerability discovery, enterprise organizations are better equipped to handle the surge than generally assumed.
The key is their ability to quickly validate findings, prioritize risk, and get available fixes into production.
Software supply chain security firm Echo recently analyzed nearly 40,000 CVE life cycles across 250 open source container projects, drawing on a year of its own platform telemetry, survey responses from more than 80 security leaders, and an independent analysis of Anthropic's Claude Mythos.
AI Has Accelerated One Side of the Equation
The results, detailed in a report titled "Mythos Readiness Report," show how AI is transforming vulnerability discovery and exploit development — something that security teams have been encountering firsthand over the past year.
Monthly CVE disclosures rose 145% over two years, from 3,173 in June 2024 to 7,765 in June 2026, partly due to the expansion of the CVE program and increasingly because of AI-assisted vulnerability discovery. On an annual basis, CVE disclosures shot up from 30,949 in 2023 to 49,979 in 2025 and, based on the numbers so far, 2026 is on track to surpass even that number.
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Echo discovered the same pattern with container base images, of which Node and Python are the most frequently used. Between January and June 2026, the number of known CVEs in Node base images surged 338%, from around 16,000 to 70,000, while for Python the numbers went from 17,500 to 45,000 in the same period.
"Vulnerabilities are now being discovered at machine speed, while remediation remains largely manual," Echo wrote in its report. "In essence, AI has dramatically accelerated one side of the equation, but the other has yet to catch up."
Echo found that Claude Mythos has fundamentally changed the economics of exploit development and made it possible for researchers and bad actors to develop a working exploit for a known vulnerability in less than one day and for under $2,000.
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