AI Is Spitting Out Working Exploits for $3.61. Microsoft Says the Old Playbook Is Dead.
A senior Microsoft security chief told Black Hat USA that AI tools have made finding and weaponising software flaws so cheap and fast that the entire industry's approach to defence needs to change, starting now.
Key points
- Microsoft's internal AI scanning tool found roughly 200 Linux kernel vulnerabilities and automatically generated working exploit code for 182 of them.
- The average cost of finding a vulnerability and building an exploit was $3.61, with a turnaround time of 21 minutes per flaw.
- Microsoft's Security Response Center is now processing and patching twice as many vulnerabilities every six weeks compared to earlier this year, a ninefold increase since March.
- A senior Microsoft engineer warned that automatically generated exploits will be "pretty commonplace" across the industry by the end of 2025.
- Switching to memory-safe programming languages, such as Rust, is one of the most effective steps vendors can take to cut the number of exploitable flaws at their root.
Software vulnerabilities have always existed. The question defenders used to rely on was: how long does it take a criminal to actually build a weapon from one? For most of the history of computer security, the answer was: a while. Long enough for a patch to arrive, for detection tools to learn, for defenders to catch up.
That buffer is shrinking fast. And Microsoft is making that argument loudly.
What exactly did Microsoft announce?
At the Black Hat USA security conference last week, David Weston, a group manager on Microsoft's Windows security team, delivered a keynote bluntly titled The End of Rare: Defending When Offense Is Cheap. The message was not subtle.
Weston described Microsoft's MDASH tool, which stands for Multi-model Agentic Scanning Harness. Think of it as a team of AI assistants that reads software code, hunts for security flaws, and then tries to build a working attack against each one, all automatically, without a human in the loop.
Pointing that tool at Microsoft's internal Azure Linux distribution produced roughly 200 previously unknown vulnerabilities in the Linux kernel, the core layer of software that manages a computer's hardware. Of those, MDASH automatically built crash-triggering proof-of-concept exploits, meaning test attacks that prove a flaw is real and usable, for 182 of them. Many went further: they became fully working attacks that could hand an attacker root access, meaning complete administrative control over the machine.
The average cost per vulnerability found and exploited: $3.61. Average time: 21 minutes.
"These are serious vulnerabilities, the kind that I used to take a year to bespoke craft," Weston said. "They're being spit out at industrial speed."
| Metric | Figure |
|---|---|
| Linux kernel flaws found by MDASH | ~200 |
| Exploit-level proofs generated automatically | 182 |
| Average cost per flaw detected and exploited | $3.61 |
| Average time to generate an exploit | 21 minutes |
| Vulnerability volume increase since March 2025 | 9x |
| Google's Android memory-safety flaw rate, 2019 | 76% |
| Google's Android memory-safety flaw rate, 2025 | Below 20% |
Should ordinary people be worried?
Not in a panic-stations way, but the trend matters. The more easily criminals can find and weaponise software flaws, the faster companies need to patch their products, and the shorter your window of safety between a flaw existing and someone actively using it against you.
Weston said Microsoft's Security Response Center is now processing and patching twice as many vulnerabilities every six weeks as it was earlier in the year, nine times the volume it handled in March. That workload increase tracks directly with rising AI tool use across the security research community, he said. It is not a Windows-specific problem: Linux, Android, and every other major operating system is seeing the same acceleration.
What does Microsoft say defenders should do differently?
Stop playing whack-a-mole, essentially. Weston's argument is that reacting to one vulnerability at a time, the standard patch-and-move-on approach, cannot keep pace when AI lets attackers find new flaws faster than defenders can fix old ones.
His preferred alternative is switching to memory-safe programming languages, which are coding tools designed so that an entire category of common mistake simply cannot happen. Rust and Golang are the main examples. Around 70% of the vulnerabilities that major vendors patch today stem from memory-safety errors, the kind that safer languages eliminate by design.
Google's experience with Android is the clearest proof point so far. After prioritising Rust for new Android code, Google reduced memory-safety vulnerabilities from 76% of all Android flaws in 2019 to below 20% in 2025, as CSO Online first detailed. Microsoft itself rewrote its Azure hypervisor, the software layer that keeps separate virtual machines isolated from one another on a shared server, in Rust and rolled it across 1.5 million virtual machines without incident.
A US government research agency called DARPA is also running a project named Tractor that automates the conversion of older C code (a widely used but memory-unsafe language) into Rust. Microsoft Research's own tool, RustAssistant, uses AI to spot and suggest fixes for Rust coding errors.
What about the limits of just rewriting code in a safer language?
Valid question. Yan Shoshitaishvili, an associate professor at Arizona State University, gave a companion keynote at the same conference that poured a little cold water on the rewrite-everything-in-Rust idea.
His team used AI-assisted tools to study OpenHarmony, the open-source software base that underpins parts of Huawei's HarmonyOS for mobile devices. They found dozens of flaws covering Bluetooth attacks, device takeovers, and location-data leaks, found faster than his team could responsibly write them up and report them.
More pointedly, when Shoshitaishvili tested a Rust rewrite of core Linux utilities, memory-safety bugs largely disappeared. But logic-level vulnerabilities, design flaws in how the software behaves, not just how it handles memory, reappeared in new forms. Safer languages are a powerful tool, not a complete cure.
Common questions
Does this mean criminals already have these AI exploit tools?
Not necessarily the exact same tools Microsoft built internally, but the underlying AI models are widely available, and independent researchers have shown similar results. Weston's point is that the barrier to building such a pipeline is now low enough that well-resourced criminal groups almost certainly have something comparable.
What should employees or ordinary users actually do right now?
Keep software and devices updated promptly, that remains the single most effective action. If a company you use announces a security patch, the window between "patch released" and "criminals actively exploiting the flaw" is getting shorter, so treating updates as optional is riskier than it used to be.
