Vulnerabilities · 76 days ago
AI Pushes Vulnerability Work Past Human Pace The break is speed. AI is now moving inside two places defenders still treat as review gates: database changes and vulnerability triage. That makes human-in-the-loop governance too slow for the volume and tempo of decisions AI can generate.
In Redgate’s 2026 database landscape report, AI use in database management rose from 15% to 44% of organizations, and a majority now accept higher data-security risk for the speed it gives them. Rapid7 says production-grade AI systems from Anthropic, OpenAI, and Google DeepMind can already discover, chain, and sometimes remediate flaws at machine speed, pushing CVE, CVSS, NVD, KEV, and EPSS workflows beyond the assumptions they were built on.
The result is a standing mismatch: more changes reach sensitive data faster, and more vulnerabilities arrive faster than manual review, scoring, and disclosure queues can absorb.
Timeline Sources 5 sources covering this story
Socket.dev Jun 30
Risky Biz Podcast: AI Agents Are Raising the Stakes for Soft...
Open source attacks are accelerating as AI coding agents pull in dependencies faster, with less human review.
Rapid7 Jun 29
Modernizing Global Vulnerability Standards For The Age Of AI
As AI-driven vulnerability discovery accelerates, the cybersecurity ecosystem is being forced to examine whether the standards, disclosure processes, and prioritization frameworks defenders rely on can still keep pace. In Rapid7’s new policy paper, understand where today’s vulnerability management infrastructure is breaking under AI-era conditions, and what governments, security companies, and frontier AI providers need to do next.
Help Net Security Jun 29
Companies keep bolting AI onto their products, and the security bill is coming due - Help Net Security
AI pentesting finds high-risk flaws at 2.7x the rate of other systems, and two of every three serious AI findings stay open and unfixed.
Help Net Security Jun 29
Most teams accept higher risk for faster AI database work - Help Net Security
AI database security is slipping as autonomous tools gain write access to sensitive data faster than governance and controls can keep up.
Dark Reading Jun 26
AI Decline? Confidence Falls in Autonomous Penetration Testing
Companies are still experimenting with automated AI systems to find security weaknesses, but fewer are relying on the technology.
Infosecurity Magazine Jun 25
Trust in Automated AI Vulnerability Scanning Collapses to 9%
Cobalt study finds 20-percentage-point drop in number of organizations relying solely on AI automation for testing
Part of the PlainSec briefing for 2026-06-30
Editions Related stories Vulnerabilities · 76 days ago
AI Pushes Vulnerability Work Past Human Pace The break is speed. AI is now moving inside two places defenders still treat as review gates: database changes and vulnerability triage. That makes human-in-the-loop governance too slow for the volume and tempo of decisions AI can generate.
In Redgate’s 2026 database landscape report, AI use in database management rose from 15% to 44% of organizations, and a majority now accept higher data-security risk for the speed it gives them. Rapid7 says production-grade AI systems from Anthropic, OpenAI, and Google DeepMind can already discover, chain, and sometimes remediate flaws at machine speed, pushing CVE, CVSS, NVD, KEV, and EPSS workflows beyond the assumptions they were built on.
The result is a standing mismatch: more changes reach sensitive data faster, and more vulnerabilities arrive faster than manual review, scoring, and disclosure queues can absorb.
Timeline Sources 5 sources covering this story
Socket.dev Jun 30
Risky Biz Podcast: AI Agents Are Raising the Stakes for Soft...
Open source attacks are accelerating as AI coding agents pull in dependencies faster, with less human review.
Rapid7 Jun 29
Modernizing Global Vulnerability Standards For The Age Of AI
As AI-driven vulnerability discovery accelerates, the cybersecurity ecosystem is being forced to examine whether the standards, disclosure processes, and prioritization frameworks defenders rely on can still keep pace. In Rapid7’s new policy paper, understand where today’s vulnerability management infrastructure is breaking under AI-era conditions, and what governments, security companies, and frontier AI providers need to do next.
Help Net Security Jun 29
Companies keep bolting AI onto their products, and the security bill is coming due - Help Net Security
AI pentesting finds high-risk flaws at 2.7x the rate of other systems, and two of every three serious AI findings stay open and unfixed.
Help Net Security Jun 29
Most teams accept higher risk for faster AI database work - Help Net Security
AI database security is slipping as autonomous tools gain write access to sensitive data faster than governance and controls can keep up.
Dark Reading Jun 26
AI Decline? Confidence Falls in Autonomous Penetration Testing
Companies are still experimenting with automated AI systems to find security weaknesses, but fewer are relying on the technology.
Infosecurity Magazine Jun 25
Trust in Automated AI Vulnerability Scanning Collapses to 9%
Cobalt study finds 20-percentage-point drop in number of organizations relying solely on AI automation for testing
Part of the PlainSec briefing for 2026-06-30
Editions Related stories