Finding bugs is no longer the bottleneck
For years, the security industry's main complaint was that it couldn't find vulnerabilities fast enough. New data suggests the problem has flipped. Discovery is accelerating, partly because of AI, and the hard part is now fixing what has already been found.
HackerOne's latest report puts a number on this. Its backlog of validated but unresolved vulnerabilities grew 131% over two years, even though organizations on the platform now remediate issues 54% faster 1. The company calls this accumulating risk "Exposure Debt" 1. Nearly 70% of security leaders surveyed said validated findings reach them faster than their teams can fix them 1. Remediation is improving, but incoming volume is growing faster.
Google sees the same curve at internet scale
Google Threat Intelligence Group (GTIG) describes a similar trend across the wider vulnerability landscape. Monthly disclosures roughly doubled during 2026, from 5,045 in January to 10,477 in July, then peaked at 10,740 in August 2. Disclosures that GTIG rates as high-risk, using its own ratings rather than CVSS, rose 167% over the same period, from 131 to 350 2.
Exploitation is also up. GTIG counted 141 distinct vulnerabilities exploited in the wild in the first eight months of 2026, more than the 127 it recorded in all of 2025. That works out to about 18 per month, up from 10.5 2. Zero-days accounted for 62% of exploited flaws. Their monthly average rose only modestly, from eight to 11, before jumping to 22 in August 2.
One figure should temper the alarm. Only 0.23% of this year's disclosed vulnerabilities, about one in 431, have been observed under exploitation 2. Most of the flood is noise from an attacker's point of view. Defenders still have to triage all of it to find the small fraction that matters.
AI is changing what gets found
HackerOne says AI is helping researchers uncover classes of bugs that traditional scanners tend to miss, including authorization flaws and multi-step attack chains 1. These are context-heavy problems that usually took experienced human testers a long time to find. They are often harder to fix than a missing patch because they can require changes to application logic.
AI systems are also becoming a target in their own right. On HackerOne's platform, reports of system prompt leakage rose 557% year over year. Misinformation reports climbed 455% and improper output handling 264% 1. Prompt injection and sensitive information disclosure are still the largest AI vulnerability categories 1. As companies connect language models to tools, data and other systems, the attack surface grows, and so does the queue of things to fix.
Where Anthropic's cyber program fits
Anthropic's latest move sits against this backdrop. The company has folded Project Glasswing into an expanded Cyber Verification Program with three access tiers 3. In the same week it released Claude Haiku 5.5 at a 75% lower cost 3. The public summary does not describe what each tier unlocks, but the direction is clear: verified security users get wider, structured access to Claude's capabilities.
That may well help defenders. But read alongside the HackerOne and Google data, tiered access to more capable models mainly addresses discovery, and discovery is the part of the pipeline that is already outrunning the rest. Cheaper, more widely available models are likely to produce more findings. On their own, they do nothing for the engineering capacity needed to close those findings out. That reading is an inference from the numbers, not a claim either company has made.
There is also an ongoing debate about how much risk AI models add on the offensive side. Researcher Nathan Lambert has argued that panic over open-weight models and cyber risk is miscalibrated. He points out that the GLM-5.3 release has not yet produced attacks 3. GTIG's data partly supports a measured view: exploitation is rising, but slowly compared with disclosure 2. The more immediate effect of AI looks like volume rather than a sudden wave of AI-built attacks.
The real metric to watch
The takeaway is that time-to-discovery is becoming a weaker measure of security health. HackerOne's 54% remediation gain looks good until it is set against a 131% backlog increase 1. Google's doubling of disclosures shows the same mismatch across the industry 2.
The programs that matter most over the next year will be the ones that help teams prioritize and remediate, not just detect. That means separating the roughly one-in-431 exploitable flaw from the rest, and making fixes cheap enough to keep pace. Until AI vendors put as much effort into the fixing side as into the finding side, Exposure Debt is likely to keep growing.
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