Securing GenAI Development with Snyk

From design to deployment, the rise in AI tools and AI-generated code is changing developers’ workflows, enabling them to focus on more creative and complex tasks. However, while 96% of developers use AI coding assistants to streamline their work, it can have a negative impact on security teams. One-fifth of AppSec teams surveyed said they face significant challenges securing AI-generated code due to how quickly it’s produced. 

As GenAI tools like ChatGPT and Copilot become increasingly prevalent in developer workflows, guardrails must be in place to ensure AppSec teams can meet demands while prioritizing security. Without the proper guardrails, AppSec teams will continue to struggle, placing organizations at an increased risk for breaches and critical vulnerabilities. 

Snyk’s newest ebook, Taming AI Code: Securing GenAI Development with Snyk, details the risks and complexities of adopting AI-generated coding tools. Learn how organizations can implement guardrails with Snyk, ensuring developers create secure AI-generated code and prevent critical vulnerabilities within their codebase.

Risks of AI-generated code

With 75.8% of developers believing that AI-generated code is more secure than human-written code​, organizations are at serious risk for critical vulnerabilities. Almost 80% of developers admit to bypassing security measures to save time, trusting that AI code meets security expectations. However, up to 40% of AI-generated code from tools like Copilot contains security flaws.

The overreliance and overconfidence of AI code means insecure code can easily spread across large codebases. Even more alarming: A recent Cloudflare report shows that after a proof of concept is released, Common Vulnerabilities and Exposures (CVEs) can be exploited in as little as 22 minutes. Without a security framework tailored to GenAI and high-speed development processes, organizations are vulnerable to significant security issues across multiple projects and codebases. 

Implementing seamless guardrails with Snyk

Traditional security solutions weren’t designed for the evolution of the modern development lifecycle or the speed of AI. Because of this, traditional tools slow down AppSec teams, causing friction between developers and security. By adopting tools specifically created to secure both human-written and AI-generated code, organizations can maintain a proactive, scalable security framework without impeding developer productivity or limiting the usage of AI. 

Proactive security 

Snyk Code enables teams to implement a developer-first approach to code security, regardless of whether it is human-written or AI-generated. Through Snyk Code, vulnerabilities are found and fixed in real time without slowing production or interrupting developer workflow. 

Here’s how Snyk Code can help AppSec teams implement proactive guardrails and avoid delays and disruptions:

• In-IDE security: Snyk Code integrates directly into the integrated development environment (IDE), enabling developers to stay in their work environment and avoid context switching. The seamless integration also enables real-time scanning to catch and fix vulnerabilities faster and earlier, preventing the spread of insecure code or security flaws. 

• AI-driven tools: Snyk’s AI-powered tools — DeepCodeAI and DeepCode AI Fix — address the challenges of securing AI-generated code using a hybrid security-trained AI model to scan code and detect and fix vulnerabilities in real time. 

• Enhanced productivity and security: With Snyk’s DeepCode AI Fix, developers aren’t required to switch tools or deal with complicated security interfaces. Snyk DeepCode AI Fix offers instant, one-click fixes to remediate code and vulnerabilities. Developers receive real-time feedback and fix suggestions, empowering them to make security decisions without hampering their workflow. 

• Accuracy and speed: Snyk’s approach helps AppSec teams balance speed and accuracy. Customer studies have shown that Synk’s approach results in 2.4x faster scans compared to traditional security solutions. Additionally, Snyk’s DeepCode AI and CodeReduce technology enhance vulnerability detection accuracy, reducing false positives and negatives and ensuring AI-generated code is accurate and secure.

The development lifecycle will continue to evolve as the adoption of AI-generated tools and processes becomes more prominent. As organizations look forward, adopting a future-proof solution to keep up with development in real time while keeping security at the forefront is necessary. 

With Snyk, organizations can ensure their AppSec teams are supported, even as new security threats and AI-drive risks emerge. To learn more about implementing guardrails for AI-generated code and future-proofing your AppSec, read Snyk’s ebook, Taming AI Code: Securing GenAI Development with Snyk.