With AI coding tools poised to transform the job of a software engineer, the question remains: how trustworthy are these models’ outputs?

While vibe coding is helping engineers be more productive than ever, the code itself isn’t always as secure as it could be. And as models become more powerful, those vulnerabilities can be easily exploited: Data from Experian, published last week, found that 40% of the 5,000 data breaches it handled last year were driven by AI. With AI creating a cybersecurity powder keg, Synthesia decided to do something about it.

On Thursday, the company published a blog post detailing its approach to automating code security reviews, offering a recipe that any company can use and retrofit to generally available models. The company claims this six-step technique achieves cybersecurity performance similar to Anthropic’s Mythos.

To break it down simply:

• The first two steps involve prepping the code to identify potential vulnerabilities and mapping every possible entry point for untrusted input.
• For the next two steps, the system sends AI agents to hunt for three types of vulnerabilities: injection attacks, authorization issues, and business logic flaws. Duplicate findings are removed, saving tokens by avoiding the need to thoroughly investigate them.
• Finally, the AI agents first double-check each vulnerability and then summarize what actually needs to be fixed.

Martin Tschammer, head of security at Synthesia, told The Deep View that this technique is a solution to a problem that the company aimed to tackle internally first. As a software firm, it’s using AI and coding agents to ship products faster than ever.

“Security review in particular depends on careful, deliberate analysis so it's exactly the kind of work that breaks down under velocity pressure,” Tschammer said.

Tschammer also said this system offers several particular advantages. For instance, rather than just understanding general code, applying this to the models you use in your enterprise means they understand your specific codebase.

It also cuts out additional work before reaching your team, and doesn’t require a frontier model to leverage. Plus, at an average of less than $4 per review, it’s an affordable way to prevent vulnerabilities from slipping through the cracks.

“You do not have to wait for Mythos, or some other security-branded model, to become available,” Tschammer said. “In fact, we believe you don’t have the luxury to wait. If you want to stay ahead of the curve, you need to act now.”

Our Deeper View

With models like Anthropic’s Mythos and OpenAI’s GPT-5.5 offering an unprecedented level of cyber capability, AI’s ability to supercharge both cyberattackers and cyberdefenders has come sharply into focus in recent months. However, vibe coding and AI broadly have empowered companies to slash their workforces and ship faster. But if the increased vulnerabilities and attacks have taught us anything, it’s that speed is the enemy of perfection. With stakeholders pressuring executives for returns, the question remains if the enticing capabilities and promise of this technology will outweigh the security risks that it poses. Will measures like the ones Synthesia is taking be enough to make a difference for your organization? It certainly can't hurt. If you're using vibe coding to build software, you're probably introducing a large number of vulnerabilities as well. So you should be prepared by taking steps like this before Mythos and GPT-5.5 arm your attackers.