Bridgewater Associates is one of the world’s largest hedge funds. Every weekday, it sends out a note to its clients entitled “Bridgewater Daily Observations.” Every so often, the firm allows us to republish, in part or in full, individual editions of its “Daily Observations.”
**What follows is the executive summary of yesterday’s edition. The subject is AI cyber risks. It was written by Hudson Attar, an investment associate, and Arham Habib, a quantitative researcher, both of whom work at Bridgewater’s headquarters in Westport, Connecticut. **
It is worth reading in full.
We don’t have all of the details related to yesterday’s Microsoft outages and series of vishing campaigns across major financial firms, but we do think that episodes like this are one flavor of disruption that is likely to become more common as the cyber-exploit exponential we write about in this piece continues to unfold. We think it is important to pay attention to major outages like this even when we aren’t sure that malicious actors are at play because waiting until it is clear that damaging attacks are getting through to key infrastructure will lead to being too late in markets. Bridgewater remains highly vigilant to these evolving risks. We will follow up on this work with another piece covering where we see potential impacts—for now, we want to share how we are tracking and processing cyber risks today.
As we discussed in our recent *Observations on AI cyber risks, cyber-hacking ability using open-source models has reached dangerous levels, and * we are managing money based on a one-in-three chance of an economically destabilizing attack within the next year. AI-enabled cyber warfare is now spreading exponentially with limited controls—like a virus. We see attacks continuing to inflect upward in spite of the race to secure software and the internet, and don’t think the potential scale of cyber warfare is well appreciated because of how hard it is to track these attacks systematically. Given that cyber warfare is on an exponential path, reasoning about it well requires staying ahead of the curve, while most decision makers don’t even have good visibility into what is happening—that is part of why we are concerned about the risk of a disaster.
Thus far, the plan for managing cyber risks hinges on using the same tools to preemptively identify and patch vulnerabilities before they can be exploited. However, executing that plan is a daunting task because of how much insecure human-written code has been produced over the last several decades and how diffuse ownership of it is. And this approach comes with its own risks in the form of potential loss of containment or misalignment.
In today’s
**Defensive efforts are uncovering vulnerabilities at an unprecedented rate, but bugs are still slipping through the cracks.**Programs like Anthropic’s Glasswing and OpenAI’s Daybreak have driven a record surge in potential exploits. But defenders have to fix every security-critical bug before it is exploited, while attackers only need to find one, and zero-day exploits (those with no lead time to discovery) have roughly doubled since the first truly cyber-capable open-source models were released. Further, not all companies have the resources or incentives to invest in such preemptive protection.**AI is allowing attackers to exploit the narrow window between when patches are developed and when they are adopted.**Patching open-source software necessarily exposes the underlying vulnerability, and every downstream user has to adopt the fix before attackers can exploit the bug. AI has made it easier for attackers to win that race. The number of recorded actively exploited vulnerabilities has surged, and the average time between disclosure and exploitation has fallen from a month to 11 days.**Policy responses in the hardest-hit economies are directionally helpful but insufficient, and in the West, they remain limited.**Japan and South Korea, which have suffered a wave of damaging attacks on financial institutions, have begun mobilizing resources. Japan has allocated ¥10 billion (about $63 million) to cyber defense, and South Korea has introduced legislation mandating executive-level chief information security officers (CISOs) and fines for repeated breaches. But neither addresses the problem that much of the internet runs on open-source software maintained by volunteers and nonprofits with limited resources.**The arms race is accelerating as AI expands the attack surface.**While frontier models comb through decades of human-written code, developers are using AI coding tools to add millions of new lines, much of them with their own bugs. Even if AI-written code is marginally safer, the sheer volume means the attack surface is growing faster than defenders can secure it.
Absent an immediate and forceful coordinated policy response, we see the pressures as lining up for the cyber warfare epidemic to get worse from here. The “head start” between Glasswing’s launch and the release of cyber-capable open-source models this summer was a one-time gift that we’re unlikely to see replicated, and its protective benefit will wane over time. Malicious actors are only starting to learn how to use AI to find and exploit vulnerabilities, and we suspect they are earlier on the learning curve than defenders, with more room to improve. Threat actors are not yet broadly deploying fully autonomous attack workflows—a human remains in the loop—but open-source models are not far from the capability level where that is likely to change.
We developed a time series of cyber incidents, a taxonomy for linking incidents to root causes, and a real-time tracking pipeline of exploits in order to monitor what is going on. We scraped public disclosures, media coverage, and corporate filings to assemble a history of past exploits and adjusted them to account for typical reporting lags for different types of players across jurisdictions. We found that the count of cyber incidents and the share of known cyber incidents attributed to AI have both skyrocketed. Following a dramatic wave of major software vulnerabilities, supply chain attacks, and AI-enabled hacking incidents, cybersecurity professionals dubbed the last month of exploits “Black October.” The charts below show how the picture since then has been ongoing exponential growth, with little likelihood of abating going forward.
These excerpts from Bridgewater Daily Observations (11/13/2026) were republished with permission from Bridgewater Associates. Permission to republish requires that we post the following “Important Disclosures and Other Information”:
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