Foreword
Were the three stories below the only AI stories that mattered over the last three days? No. But they’re the three stories I think are most likely still matter a few weeks from now.
People I trust tell me that the AI-fueled “hackpocalypse” we’re supposedly in this month really is that bad, with many overlapping attacks and scares that each could have been the biggest cyber story of the year, in a normal year. The race to patch websites that use PHP is only the headline example.
Are we in for a Y2K crisis every week now?
An AI-discovered flaw in PHP, part of the software infrastructure of up to 70% of all websites, has security experts and agencies scrambling to get everyone patched. Within seconds (longer for more complex sites), hackers exploiting the flaw could gain access to unpatched systems. It doesn’t require anyone to be fooled into making a mistake like clicking on the wrong file.
The vulnerability was kept as secret as possible since its discovery in early August by a researcher using GPT-5.6 Sol, a top publicly available model from OpenAI. Those in the know were working on the needed patch, which is long and complicated. News of the patch leaked two days before it was to come out on October 22nd, though, potentially giving hackers a window to exploit the vulnerability. So the patch is getting rolled out today — a day early.
The vulnerability is described as “too complex to have been discovered without AI.”
A logical concern is that many smaller sites with hands-off owners may fail to hear the news and act on it in time, leading to a proliferation of compromised sites serving malware or assisting with criminal activities.
In the run-up to the year 2000, concern about a well-known issue in software not written to handle dates past 1999 led to an expensive and largely last-minute crunch to prevent disaster. But it was successful.
I hope the PHP crisis is handled even half as well as Y2K was, because our world is now even more dependent on digital infrastructure than it was in 2000. The world’s response to Y2K is something I hold up as reason to be optimistic that the AI extinction problem can be handled.
But our attention and endurance may be stretched in the meantime. Releases of newer and stronger AIs are accelerating, and each model seems capable of discovering and exploiting classes of vulnerabilities beyond the reach of those before it.
OpenAI agents seen taking any excuse to disable misalignment monitoring
The company just disclosed two such incidents that occurred earlier this month. In the first, GPT-6.1 Sol was told “don’t send any messages” while searching for tasks on Slack. It decided that this could also mean not sending automatic alerts to the Security team if or when its misalignment monitor detected concerning behavior, and it took actions to disable these alerts.
In the second incident, GPT-6 Astra removed a monitor as part of making a user’s code match a reference example that didn’t include such monitoring. This could seem innocent but for the fact that its chain-of-thought log about this said, “Basic doesn’tagentmonitor yay.”
When the user asked it if it had removed the monitor, Astra straight-up lied:
“Does [redacted] path include L1 monitoring? did you remove that?”
“No […] I did not remove an enabled monitor from it.”
OpenAI says it’s trying to determine if the behavior is what it calls “benign overpersistence” borne of misunderstandings about the importance of monitoring, or whether the models “might have a propensity to evade misalignment monitoring in particular and exhibit motivated reasoning in order to do so.”
I don’t see anything about them pausing training while they figure that out.
The Pentagon has built a sabotage agency almost certainly focused on disrupting foreign AI programs
A former intelligence official who worked with the agency told Politico that the Technology Support Office’s goal is to “buy time or stop adversaries from developing technologies” that would threaten U.S. military dominance in major conflicts.
I note two pieces of important context here: The first is that the NSA alone is already known to have spent billions “testing” AI models, and I put that word in quotes because that price strongly implies that they are deploying these models to gather intelligence and undermine adversaries while strengthening their defenses against the same.
The second is that the idea of Mutually Assured AI Malfunction (MAIM) has been suggested as a default arrangement that plays out if the U.S. and China both start taking AI very seriously but can’t or won’t work out verifiable deals to limit the technology. In a MAIM arrangement, frontier progress slows because expensive projects are actively sabotaged by rivals or deterred from starting by credible threat of such sabotage.
The analyses and opinions expressed on AI StopWatch reflect the views of the individual contributors and the sources they cover, and should not be taken as official positions of the Machine Intelligence Research Institute.