Announcing the Save CTFs Fund | OtterSec Introduction

OtterSec is announcing the Save CTFs Fund , a $100,000 commitment to keep CTFs competitive in the age of AI.

We’ve always been passionate about CTFs. Our team would not exist without them. However, as the year has been progressing, the state of CTFs, to put it bluntly, is depressing. You spend months working on a novel challenge, and a new model comes out a day before the CTF and one-shots the challenge. The current progress in AI development has led to CTFs becoming pay-to-win.

We think (hope) this is solvable. Hence, in 2026, we are being much more selective about sponsoring Jeopardy CTFs, and encourage other companies to do the same. Instead, we’re funding new ideas where the leaderboard still means something. Even if AI is involved. Especially if AI is involved.

TL;DR

AI one-shots most Jeopardy challenges now. A Jeopardy leaderboard increasingly measures token budget rather than skill.

The fix is not “ban AI,” and it’s not “run AD lol.” We believe the fix involves creating challenges that enable more granular measurement of how a solution performs compared to other teams. An example can be found in “An example challenge.”

We’re funding experiments. We’re also shipping some interesting features in rCTF v2 that allow you to build challenges with more granular scoring.

Think you have an idea that can save CTFs? We’d love to sponsor it! Send a one-pager to ctfs@osec.io that meets the requirements outlined in “How to ask for a sponsorship.”

What is the point of CTFs?

Firstly, an introduction to CTFs is in order: CTFs, also known as Capture The Flags, are an interesting phenomenon in which intrinsically motivated authors propose intellectual problems that usually involve computers (but not necessarily!) at events that can range from a couple of hours to a couple of days. Players learn through these problems how systems break, fit together, and bend to their own will in order to capture a piece of text known as a flag. This often inspires the same players to become authors, resulting in the lively scene we see today.1

The main point of CTFs is the educational value they provide: the feedback loop is very tight and rewarding. You attempt to solve a challenge, you fail, and you read someone else’s write-up. At some point, you’re the one writing write-ups to help others, and you’re also the one going up on the stage for LiveCTF at DEFCON.

The second point is rewards : you get bragging rights, sometimes money, sometimes licenses, and the most sought-after reward is flights (and accommodation) to an on-site finals event. And although these rewards might not be much relative to the raw amount of knowledge you acquire from doing these activities, the overwhelming majority of the community consists of students, which means the stakes are high.

How AI flattens the skill curve in CTFs<br>A line chart with player skill on the x-axis and results on the y-axis. Before AI, results rise steadily with skill from a low base. With AI, even low-skill players start high and the curve stays nearly flat across the middle, rising sharply only at the very top end of skill.<br>results (score, solves)

before AI

with AI

player skill →

AI breaks the loop completely. It flattens the skill curve by solving the challenge for you, then provides a write-up, making many challenges’ write-ups available. Since there are stakes involved, there is no incentive not to use them during the live event. Hence, now, only the most talented can compete, since the only valuable challenges are very hard challenges that are out of reach for LLMs, with no clear path for new players to compete without seriously sacrificing growth, which won’t be visible on the leaderboard for a long time compared to pre-LLM.

This also affects the organizers. Challenges are the most important part of a CTF. Someone needs to write them. Now if the write-up is available as soon as the challenge is released, what is the point of writing a challenge, with the explicit intent of teaching someone something, when you will receive no feedback on your challenge, since in the context of a competition, it’s better to solve it with an LLM than to attempt it manually.

The state of Jeopardy

What was an early warning shot in DEFCON CTF 20252 has accelerated today with people declaring the death of CTFs.3

Renwa<br>@RenwaX23

"Dad, what was it like playing CTFs before AI?"

7:34 PM · May 24, 2026 · 121.7K Views

21<br>274<br>1.5K<br>275

And it shows up in the data. The gap between the best teams and the rest of the top 10 has been quietly compressing across every tier of event:

With the release of GPT-5.5, the public now has access to models that are better than the average CTF player. Starting from this model and beyond, anything that was considered a medium-hard CTF challenge4 is one-shottable.

You simply cannot outwrite this cadence of improvement in large language models. Simply making the challenges harder is not reasonable; it’s...