Apple has introduced limits on how many security reports researchers can have open simultaneously, and once they reach that threshold, they may need to wait 30 days before submitting another potentially serious software vulnerability through the company's internal security portal. The company rolled out the restrictions in June after being overwhelmed by AI-assisted reports, many of which turned out to be what Apple calls "AI slop"—submissions that weren't genuine vulnerabilities. Italian cybersecurity firm Bynario highlighted the new policy after hitting the limit, and according to the Financial Times, the company used GPT-5.5 through its Atlas platform to identify more than 50 possible bugs in Apple's newest Mac operating system in just three weeks.
One vulnerability Bynario discovered was a flaw in macOS Screen Sharing that could let an authenticated VNC user access protected data and create files with root privileges—Apple assigned it CVE-2026-43760 and patched it in macOS Tahoe 26.6. Bynario said it couldn't report the flaw initially because it had already reached Apple's cap for open investigations. Apple's latest updates contained roughly five times as many security fixes as earlier release cycles. Bug bounty platform HackerOne already uses AI to conduct the first review of incoming vulnerability reports through a service called Hai Triage, which can review a report in minutes and decide if it's likely valid, invalid, or needs additional checking. Meanwhile, a separate vulnerability in Apple's Hide My Email feature—first reported by EasyOptOuts co-founder Tyler Murphy in June 2025—went unpatched for a year, and AppleInsider reproduced the behavior on July 17, 2026, two weeks after Apple claimed it had deployed a fix.
Apple's Security Bounty guidelines warn that researchers who repeatedly submit ineligible reports, including theoretical flaws discovered by AI without proper validation, may have their reports paused for 180 days, and researchers with more than two paused periods may be removed from the program permanently. A human reviews every security issue reported to Apple, even though the company uses AI to help sort reports when there are too many, and if researchers hit the cap, they can ask Apple to raise it. The report notes that HackerOne says Hai Triage does not make the final call, and all outcomes are reviewed or confirmed by human analysts, who remain responsible for deciding whether a vulnerability is real.
The challenge is that AI-powered tools can now uncover possible flaws and write them up faster than security teams can determine whether they're genuine, compressing work that once took weeks into minutes. Apple has deployed the technology internally to find vulnerabilities in its own software, but submission caps don't distinguish between convincing AI-generated reports and real security flaws found with AI, causing both to compete for the attention of security teams. The cost of running these AI-driven workflows is falling fast enough that volume is becoming the default, which only accelerates the triage bottleneck. Using AI to sort these reports could help clear the backlog, but it could also bury a vulnerability if the system mistakes it for "AI slop." The report notes that researchers with a track record of finding real bugs could be allowed to submit more, while those using AI could be asked to prove the flaw can be reproduced—Apple already asks for affected software versions, steps to reproduce the issue, and a proof of concept or exploit.
Security teams were already having trouble investigating and fixing real vulnerabilities before AI caused the number of reports to jump, and the report highlights that blunt caps risk holding up legitimate reports while doing little to stop convincing ones that turn out to be wrong. Apple's approach to AI extends beyond security—the company recently turned Safari into a platform AI agents can control, which highlights the shift in how it integrates AI into its product infrastructure. That ambition makes the security pipeline problem more urgent: as Apple builds more AI-driven surfaces, it also needs to keep up with the vulnerability reports they attract. Without a way to prioritize by researcher track record, the cap could delay genuine security disclosures that matter. The trade-off companies face is between managing overwhelming report volume and maintaining pathways for legitimate security research—a tension that will only sharpen as automated tooling becomes cheaper and more accessible. Submission limits may address symptom rather than cause, forcing security programs to rethink how they credential and prioritize researchers in an era where anyone can spin up analysis at scale.