In the age of AI-generated code and the growing reuse of open-source software components, organizations need to adopt a security first strategy to save money, reducing conflict, and build better software.
I doubt anyone would argue that strong security is critical to successful digital transformation plans and deployments. Yet for too long, security has been treated as a final gate, something to check off at the end of the development process. This reactive approach has led to increased conflict between development and security teams, missed vulnerabilities, and unnecessary costs. But what if security could be integrated earlier, continuously, and in a way that empowers developers instead of creating roadblocks?
See also: In Defense of Keeping a Human in the AI Loop
In a recent Dev Interrupted podcast, hosts Andrew Zigler and Ben Lloyd Pearson looked into some of the most pressing issues surrounding AI in tech with guest Tanya Janca from SheHacksPurple and author of “Alice and Bob Learn Secure Coding.” Let’s explore how transforming security into an ongoing practice (starting from clear, actionable requirements and incorporating continuous learning habits) can save money, reduce conflict, and result in better, more secure software.
The Case for Shifting Security Left: A Proactive Approach
Traditionally, security has been treated as a final checkpoint in the software development lifecycle (SDLC), something to be considered just before release. Developers would build features, write code, and then hand it off to the security team for testing. This is fine if nothing flags as a security risk. However, if security issues are found, it often leads to delays and conflicts as developers scramble to fix problems at the last minute. At the end of the day, this approach creates friction in the best-case scenarios. And the worst? Overlooking security vulnerabilities until it was too late.
However, integrating security earlier in the process, often called “shift-left security,” can significantly reduce these issues. By embedding security practices from design to deployment, organizations can identify vulnerabilities early, reduce the risk of attacks, and prevent costly last-minute fixes.
How Clear Requirements Empower Developers and Save Money
One of the keys to making security an ongoing practice is establishing precise, actionable security requirements from the beginning. By providing developers with specific, easy-to-follow guidelines on how to meet security standards, organizations can reduce confusion, lower the risk of errors, and streamline development processes.
Janca advocates for creating internal knowledge libraries that provide clear documentation and best practices for developers. These libraries can include everything from secure coding guidelines to checklists for security scanning tools, allowing developers to make security a part of their everyday work rather than a hurdle to overcome at the end.
By proactively designing secure features, enforcing security requirements, and giving developers the tools to implement them, organizations build better software and save money. Addressing security early on reduces the chances of costly breaches and the need for expensive rework down the line. More importantly, it creates a culture of security, ensuring that security practices are embedded in the development process, not just bolted on at the end.
See also: Navigating the New Cloud Security Landscape
Fostering Continuous Learning Habits to Build Stronger Security Practices
Security is neither a one-time task nor something that can be solved by simply installing a tool and running a quick test. It’s an ongoing practice that requires continuous learning and adaptation. In the world of fast-paced software development, staying up to date on the latest security threats, best practices, and tools is essential.
Janca recommends dedicating time for ongoing learning within development teams. For example, organizations can carve out a weekly learning block where developers are encouraged to explore new security concepts, take online courses, or review case studies of past vulnerabilities. This habit keeps developers sharp and empowers them to take security into their own hands, making it part of their daily workflow rather than a separate concern.
One way to support this continuous learning is by building internal knowledge repositories. These libraries can house everything from secure coding best practices to security threat models, which are easily accessible to developers when needed. By giving developers easy access to the right resources, teams can consistently improve their security practices, ensuring they are equipped to handle emerging threats.
Evaluating AI-Generated Code for Security
As AI tools become more integrated into the development process, the potential for automation in coding has grown. AI can help generate code, automate tests, and even suggest optimizations. However, relying on AI-generated code without critically evaluating it can introduce significant security risks.
AI is powerful, but it’s not perfect. AI models can make mistakes, especially in complex areas like security. Janca stresses the importance of thoroughly reviewing AI-generated code before integrating it into production. Developers should not assume that AI-generated code is secure simply because an algorithm produced it. Instead, they should apply the same security standards and testing practices they would use for human-written code.
This includes performing static analysis, running vulnerability scanners, and conducting peer reviews to ensure the code meets security standards. Additionally, developers should remain skeptical of AI-generated suggestions and use their own judgment to evaluate the code’s efficacy.
See also: AI Security Leaderboard Reveals Model Cybersecurity
Concrete Steps for Developers and Leaders
A security-driven culture isn’t accidental. Here are some things companies can do to build one.
- Develop Clear, Actionable Security Requirements: Provide developers with specific security guidelines and requirements at the start of a project. This includes defining security standards, best practices, and tools to be used throughout the development process.
- Foster Continuous Learning: Encourage developers to dedicate time each week to learning about new security threats, best practices, and tools. Consider implementing regular “learning blocks” or internal training sessions to keep security top of mind.
- Build Internal Knowledge Libraries: Create a central repository of secure coding guidelines, best practices, and threat models that developers can easily access. This empowers developers to implement security throughout the development process without waiting for external input.
- Evaluate AI-Generated Code Critically: AI can be a powerful tool, but it’s important not to rely on it blindly. Always review AI-generated code for security vulnerabilities and run tests to ensure it meets security standards.
- Make Security Part of the Culture: Security should be everyone’s responsibility. From developers to leadership, creating a culture where security is woven into the fabric of the development process will lead to better, more secure software—and reduce conflict between teams.
Building Better Software Through Security
Transforming security from a final gate into an ongoing practice is essential for building better, more secure software. By providing developers with clear requirements, fostering continuous learning, and critically evaluating AI-generated code, organizations can save money, reduce conflict, improve security, and create a stronger development culture. Security is not just a task to complete—it’s a habit to develop, and organizations that embrace this shift will be better prepared for the challenges of the AI-driven future.
