New year, new security goals: Improve your AppSec in 2025

As the clock ticks closer to 2025, we’re all trying to brainstorm goals and resolutions for the new year. But unlike the annual pledge to exercise more and eat fewer sweets around the holidays (whoops), application security is one area where nobody can afford to slip up. 

Let’s skip the procrastination phase and hit the ground running with some practical New Year’s resolutions that will help you step up your AppSec game.

Resolve to fix vulnerabilities faster 

The process of identifying, prioritizing, and patching vulnerabilities is often slow and resource-intensive. Not to mention that the gap between vulnerabilities discovered and vulnerabilities remediated is widening. While the typical enterprise only has a compound vulnerability remediation rate of 5% per month, CVE volumes are growing approximately 25% on an annual basis. 

This year, make it a priority to adopt workflows and tools that enable automated vulnerability fixes. Snyk’s auto-fix capabilities, for example, can quickly identify and address vulnerabilities in your code, dependencies, containers, and infrastructure as code (IaC). By integrating automated tools into your CI/CD pipelines, you can maintain strong security without slowing down your development process. 

Balance AI and automation with human expertise 

AI tools are transforming how organizations tackle AppSec, enabling faster vulnerability detection and remediation. But the most effective strategies don’t rely on AI alone — they combine AI’s speed and precision with human expertise. This collaboration builds not only stronger defenses but also trust in the growing role of AI in the security space.

To maximize the value of AI-powered security, seek out solutions that provide:

• Seamless integration: AI security solutions must integrate directly into development workflows, allowing security to meet software teams where they are.

• Actionable insights: AI tools should clearly explain vulnerabilities and suggested fixes, making it easier for developers to act quickly.

• Human validation: Like all developer security tools, AI solutions should foster trust by allowing devs to review and refine their recommendations to confirm accuracy and relevance. After all, these tools are meant to act as guardrails, not handcuffs. 

Increase trust in AI-generated code 

AI tools are also helping teams write, optimize, and debug code faster than ever before. But with speed and automation come new concerns: Can developers trust AI-generated code to meet security standards? According to our AI Code Security Report, over half (56.4%) of developers frequently encounter security issues in AI-generated code, yet 80% still bypass their organizations’ AI code security policies to use these tools. 

The key to building trust in AI-generated code is integrating security testing and remediation into the development process from the start. When AI tools provide not only code suggestions but also real-time security checks, developers can rest easy knowing that vulnerabilities are flagged and addressed as code is written (rather than discovered later during audits or in production). 

Make AI model security a habit  

If your business develops AI as part of its products or operations, securing AI models should be a top priority. These models introduce unique risks, such as model poisoning, adversarial attacks, and data drift, which can compromise both the integrity of the systems and the data they process. 

To keep your organization and customers safe, follow best practices such as: 

• Protect training data: Ensure your data pipelines are secure to prevent unauthorized manipulation or poisoning of training datasets. Utilize diverse datasets to minimize the impact of any single corrupted data source. 

• Monitor for data drift: Continuously evaluate and retrain models to address shifts in data patterns that can degrade performance and security. You can also use AI itself to help here—ML models like isolation forests can be used to detect anomalies.

• Implement model hardening: Use techniques like differential privacy, encryption, and adversarial training to make your models more resistant to attacks.

  Cheers to stronger AppSec in 2025 

  As you update your security strategy for 2025, make these AppSec improvements the New Year’s resolutions that stick. By automating vulnerability remediation, integrating security into AI-powered workflows, and safeguarding AI models, you’re not just responding to today’s challenges — you’re preparing for the software development world of tomorrow. 

  
  To learn more about “AppSec exhaustion” and how your business can engage developers in more secure coding practices, download our latest State of Open Source Security report.