Overrun with AI slop, cURL scraps bug bounties to ensure "intact mental health" - A Developer's Story

By Andrew · January 25, 2026 · 11 min read

overrunwithslop,curlscraps

When Bug Bounties Break: How AI-Generated Reports Are Destroying Security Programs from the Inside

What happens when the very systems designed to make software more secure become vectors for noise, frustration, and burnout? The cURL project just gave us a stark answer: you shut them down entirely.

After years of running a bug bounty program, Daniel Stenberg, cURL's maintainer, pulled the plug with a message that should send shivers through the security community: the flood of AI-generated garbage submissions had made the program unsustainable, threatening the mental health of maintainers who were drowning in synthetic slop masquerading as security research.

Project visualization

This isn't just another story about AI making things worse—it's a canary in the coal mine for how generative AI is fundamentally breaking the social contracts that underpin open source security.

When one of the internet's most critical projects, used by virtually every connected device on the planet, decides that bug bounties are doing more harm than good, we need to pay attention.

The Rise and Fall of cURL's Security Experiment

To understand why this matters, you need to understand what cURL is and why its bug bounty program seemed like such a good idea.

cURL is the Swiss Army knife of data transfer—a command-line tool and library that handles everything from HTTP requests to FTP transfers.

It's embedded in cars, phones, televisions, routers, and printers. It's in your PlayStation and your payment terminal. NASA uses it on Mars.

When you run `apt-get` on Linux or `brew` on macOS, cURL is working behind the scenes. The project processes literally trillions of internet transfers daily.

For a project this critical, security isn't optional—it's existential. That's why in 2019, cURL partnered with bug bounty platforms to formalize security research.

The logic was sound: incentivize security researchers to find vulnerabilities before malicious actors do. Pay them for their time and expertise. Create a structured channel for responsible disclosure.

It's a model that's worked for companies like Google, Microsoft, and Facebook, where dedicated security teams can process and validate reports.

But cURL isn't Google. It's maintained primarily by Daniel Stenberg, who has been developing it since 1998, along with a small group of contributors.

There's no security team, no tier-one support, no army of engineers to triage reports. It's just dedicated maintainers trying to keep one of the internet's foundational tools secure and functional.

The bug bounty program initially delivered on its promise. Real vulnerabilities were found and fixed. Security researchers got paid for valuable work. The project became more robust.

But then came 2023, and with it, the widespread availability of large language models capable of generating plausible-sounding technical content.

Suddenly, the careful balance that made bug bounties work started to collapse.

The Anatomy of AI-Generated Security Theater

The problem isn't just that people are using AI to generate bug reports—it's that they're doing it at scale, without understanding, and without conscience.

Stenberg describes receiving reports that look legitimate at first glance but fall apart under scrutiny.

These aren't obvious spam; they're sophisticated enough to require real time and mental energy to evaluate and dismiss.

Here's what a typical AI-generated security report might look like: It starts with confident technical language, references real functions in the codebase, describes a plausible vulnerability class like buffer overflow or injection attack, and even includes what appears to be proof-of-concept code.

But dig deeper, and you find the function names don't exist, the code paths are impossible, and the vulnerability describes behavior that cURL simply doesn't exhibit.

The reports often demonstrate what researchers call "hallucinated expertise"—the AI has learned the structure and vocabulary of security reports but lacks the actual understanding to identify real vulnerabilities.

It's like a medical student who has memorized all the terminology but has never actually examined a patient. They can describe symptoms convincingly, but their diagnoses are fantasy.

What makes this particularly insidious is that maintainers can't simply auto-reject these reports.

Each one could theoretically be legitimate, and the stakes are too high to ignore potential security issues.

So Stenberg and other maintainers found themselves spending hours every week carefully examining submissions that were increasingly likely to be AI-generated nonsense.

It's intellectual pollution—requiring real human effort to clean up synthetic waste.

The psychological toll is severe.

Imagine being responsible for software that underpins global communications infrastructure, knowing that a missed vulnerability could affect billions of devices, and then spending your limited time and mental energy debugging reports written by machines pretending to be security researchers.

It's not just frustrating; it's demoralizing.

Every hour spent on a fake report is an hour not spent on actual development, real security improvements, or the thousand other tasks that keep an open source project alive.

Why This Is Everyone's Problem

The cURL situation isn't an isolated incident—it's the leading edge of a crisis facing the entire security ecosystem.

Bug bounty platforms are seeing explosive growth in low-quality, likely AI-generated submissions.

HackerOne, Bugcrowd, and other platforms report significant increases in reports that are technically formatted correctly but contain no actual vulnerabilities.

Some researchers estimate that 30-40% of submissions on major platforms are now AI-assisted or fully AI-generated.

For large corporations with dedicated security teams, this is an annoyance that increases costs. For open source projects, it's an existential threat. The economics simply don't work.

When Google receives a thousand fake bug reports, they have teams to process them. When cURL receives a hundred, it might mean Stenberg doesn't sleep for a week.

This dynamic is particularly toxic because it exploits the conscientiousness of maintainers.

The people who maintain critical open source infrastructure tend to be deeply committed to security and reliability. They can't just ignore potential vulnerabilities.

So bad actors can effectively conduct denial-of-service attacks on maintainer attention—flooding them with plausible-looking reports that must be investigated.

The perverse incentives are obvious. Bug bounty programs pay for valid reports, creating a lottery system where submitting many reports increases your chances of accidentally hitting something real.

With AI, the marginal cost of generating a report drops to nearly zero. Why spend hours on real security research when you can generate hundreds of reports in minutes and hope one sticks?

We're watching the tragedy of the commons play out in real-time.

The shared resource—maintainer attention and the bug bounty ecosystem—is being depleted by actors who contribute nothing but extract value.

And unlike traditional spam, which can often be filtered automatically, each security report requires human expertise to evaluate.

The Implications: A Security Ecosystem in Crisis

cURL's decision to end its bug bounty program isn't just about one project—it's a signal that our current model of crowdsourced security research is breaking down.

If projects like cURL can't make bug bounties work, what hope do smaller projects have?

The immediate implications are sobering. Without formal bug bounty programs, critical projects may receive fewer legitimate security reports.

Researchers who are motivated primarily by bounties might focus their attention elsewhere.

Vulnerabilities that would have been found and responsibly disclosed might instead linger undiscovered—or worse, be found by malicious actors first.

But the longer-term implications are even more concerning. We're seeing the beginning of a retreat from open, collaborative security research.

Projects are raising the barriers to participation, requiring reputation systems, proof of past contributions, or invitation-only programs.

The democratic ideal of "anyone can contribute to security" is giving way to gatekeeping and credentialism.

This shift fundamentally changes the economics and ethics of security research.

Young researchers, international contributors, and those without established reputations may find it harder to participate.

The diversity of perspectives that makes crowdsourced security valuable starts to narrow. We risk creating an old boys' club of established researchers while shutting out the next generation.

For the AI industry, this should be a wake-up call. The same technologies celebrated for democratizing access to knowledge and capabilities are being weaponized to destroy collaborative systems.

Every LLM provider that makes it easy to generate technical content without understanding bears some responsibility for this pollution.

The "move fast and break things" ethos looks different when what you're breaking is the mental health of the people maintaining your digital infrastructure.

What's Next: Rebuilding Trust in a Post-AI World

The cURL incident won't be the last high-profile rejection of bug bounties—it's likely the first of many.

As more projects reach their breaking point, we'll see a fundamental restructuring of how security research is incentivized and validated.

Several potential solutions are emerging, though none are perfect. Platforms are experimenting with reputation systems that weight reports from established researchers more heavily.

Some are implementing "proof of work" requirements—making reporters solve technical challenges before submitting.

Others are exploring cryptographic attestation that reports were human-generated, though this arms race seems destined to fail as AI becomes more sophisticated.

The most promising approaches focus on changing incentives rather than just adding filters.

Some projects are moving to invitation-only programs where researchers must establish credibility before participating.

Others are shifting from paying for bugs to paying for audit time—compensating researchers for effort rather than just results. This reduces the lottery mentality that encourages mass submission.

Project visualization

We might also see the rise of professional security cooperatives—groups of vetted researchers who pool resources and share bounties.

This creates accountability and peer review, making it harder for bad actors to flood the system.

It's a return to the guild model, where reputation and peer endorsement matter more than anonymous submission.

The development community needs to reckon with an uncomfortable truth: the age of purely open, trustless collaboration might be ending.

The same technologies that allow us to generate code at unprecedented speed are forcing us to rebuild human verification into our processes.

It's a profound irony—AI was supposed to augment human intelligence, but instead, we're spending more time than ever proving we're actually human.

For individual developers and security researchers, the message is clear: reputation and demonstrated expertise matter more than ever.

Building a track record of quality contributions, maintaining a professional presence, and being part of the community aren't just nice-to-haves—they're becoming essential for participation.

The days of anonymous, drive-by bug bounty submissions are numbered.

The cURL project will continue, of course. Stenberg and his team aren't giving up on security—they're just acknowledging that the current model is broken.

They'll still accept security reports through traditional channels, still work with researchers, still fix vulnerabilities.

But they're doing it on terms that preserve their sanity and the project's sustainability.

This might actually be the most important lesson from this entire episode: sometimes the bravest thing a project can do is admit that a popular practice isn't working and have the courage to stop.

In a world where everyone insists that bug bounties are essential for security, cURL is saying "not like this." That's not giving up—it's growing up.

The question now is whether the rest of the ecosystem will learn from cURL's experience or whether we'll watch project after project burn out under the weight of synthetic submissions.

The answer will determine whether open source security research remains viable or becomes yet another casualty of the AI revolution's unintended consequences.

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