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AI and Cybersecurity in 2024 – What’s Changing and Why It Matters

Avatar photo by Thomas Segura on December 20, 2023

AI and Cybersecurity in 2024 - What's Changing and Why It Matters

As 2024 unfolds, the cybersecurity landscape is witnessing a notable transformation, primarily driven by the increasing integration of Artificial Intelligence (AI). Here's a deeper dive into what these changes entail and their significance in the cyber world.

The New Regulatory Landscape: Navigating Major Shifts

One of the most significant changes we're seeing is in the regulatory framework governing cybersecurity. Public companies are now required to report cybersecurity incidents within just four business days, marking a significant shift in corporate governance and cybersecurity management. This new mandate is reshaping how businesses approach cybersecurity, with a strong emphasis on compliance and proactive management of cybersecurity risks.

In parallel, the EU has taken a pioneering step by passing the first regulation specifically targeting AI technology. Although it might seem early, the groundwork for this law began back in 2021, and it has since been refined for the realities of a post-ChatGPT world. The AI Act establishes the EU as a leader in coordinating compliance, implementation, and enforcement of AI regulations.

The act sets mandatory regulations for AI, focusing particularly on foundation models. These are the most powerful systems, like GPT-4, Claude, or Gemini, developed using extensive datasets that may include billions of items, some of which could be subject to copyright. Given their potential impact, these models will face heightened scrutiny, particularly in terms of security.

Echoing the influence of the General Data Protection Regulation (GDPR), the AI Act is poised to become a global benchmark for AI regulation. The EU's proactive stance in this area demonstrates its ambition to be the world's leading tech regulator, potentially influencing global standards in AI governance.

AI's Dual Role in Cybersecurity

The role of AI in cybersecurity is a complex one. On one hand, AI technologies offer enhanced protection for systems and data. They allow for more sophisticated and efficient security measures. On the other hand, they introduce new kinds of risks and vulnerabilities. This duality is at the heart of strategic planning for CISOs and CSOs, who now have to consider both the advantages and the potential threats posed by AI. Balancing these aspects is crucial for developing effective cybersecurity strategies.

The Evolution and Scrutiny of AI Developer Tools

AI-based tools like Copilot and CodeWhisperer are revolutionizing the way developers work, significantly boosting productivity. However, these tools often bypass traditional security practices, potentially leading to new vulnerabilities. In response to this, we expect to see the emergence of oversight tools specifically aimed at scrutinizing and enhancing the security and quality of AI-generated code. This development is crucial in maintaining the balance between efficiency and security in software development.

The Rising Importance of Generative AI in Cybersecurity Products

Generative AI is quickly becoming an integral part of cybersecurity solutions. Its transition from an optional feature to a core component in both B2B and B2C cybersecurity products reflects the growing reliance on AI for advanced threat detection and response mechanisms. This trend will probably only get stronger next year, as we are yet to see LLM-first products claim superior workflows compared to traditional products.

The Evolving Responsibilities of CISOs

The responsibilities of Chief Information Security Officers (CISOs) are changing quickly due to an increasing attack surface and the need for ongoing security vigilance. With new regulations aiming to accurately reflect the cost of cyber risks in market dynamics, CISOs are under greater pressure to be proactive in risk identification and mitigation. This heightened focus is also a response to the board's growing demand for a transparent and accurate understanding of the organization's actual security stance. The ongoing SEC vs SolarWinds case, dubbed as the 'Enron moment' of cybersecurity, should definitely make a turning point.

AI, Open-Source, and Compliance

The integration of AI in cybersecurity brings to the fore the challenge of managing open-source software in compliance with new regulations. This challenge is reminiscent of the complexities faced in the implementation of the EU's Cyber Resilience Act. As regulations become more stringent, the task of ensuring that AI and open-source software meet these new standards becomes increasingly significant and complex.

In Conclusion: Striking a Balance in 2024

In summary, 2024 is a pivotal year in the field of cybersecurity, with AI playing a central role. The key to success in this evolving landscape lies in finding a balance – leveraging AI for innovation and enhanced security, while also navigating the challenges of new regulations and the inherent risks of AI technologies. It's a delicate balancing act, but one that is crucial for building a secure and resilient digital future.

*** This is a Security Bloggers Network syndicated blog from GitGuardian Blog - Automated Secrets Detection authored by Thomas Segura. Read the original post at: https://blog.gitguardian.com/ai-and-cybersecurity-in-2024-whats-changing-and-why-it-matters/

Thomas Segura
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Thomas Segura

What You Need to Scale AppSec Thomas Segura - Content Writer @ GitGuardian Author Bio Thomas has worked both as an analyst and as a software engineer consultant for various big French companies. His passion for tech and open source led him to join GitGuardian as technical content writer. He focuses now on clarifying the transformative changes that cybersecurity and software are going through. Website:https://www.gitguardian.com/ Twitter handle: https://twitter.com/GitGuardian Linkedin: https://www.linkedin.com/company/gitguardian Introduction Security is a dilemma for many leaders. On the one hand, it is largely recognized as an essential feature. On the other hand, it does not drive business. Of course, as we mature, security can become a business enabler. But the roadmap is unclear. With the rise of agile practices, DevOps and the cloud, development timeframes have been considerably compressed, but application security remains essentially the same. DevSecOps emerged as an answer to this dilemma. Its promise consists literally in inserting security principles, practices, and tools into the DevOps activity stream, reducing risk without compromising deliverability. Therefore there is a question that many are asking: why isn't DevSecOps already the norm? As we analyzed in our latest report DevSecOps: Protecting the Modern Software Factory, the answer can be summarized as follows: only by enabling new capacities across Dev, Sec and Ops teams can the culture be changed. This post will help provide a high-level overview of the prerequisite steps needed to scale up application security across departments and enable such capabilities. From requirements to expectations Scaling application security is a company-wide project that requires thorough thinking before an y decision is made. A first-hand requirement is to talk to product and engineering teams to understand the current global AppSec maturity. The objective at this point is to be sure to have a comprehensive understanding of how your products are made (the processes, tools, components, and stacks involved). Mapping development tools and practices will require time to have the best visibility possible. They should include product development practices and the perceived risk awareness/appetite from managers. One of your objectives would be to nudge them so they take into account security in every decision they make for their products, and maybe end up thinking like adversaries. You should be able to derive security requirements from the different perceptual risks you are going to encounter. Your job is to consolidate these into a common set for all applications, setting goals to align the different teams collaborating to build your product(s). Communicating transparently with all relevant stakeholders (CISO, technical security, product owner, and development leads) about goals and expectations is essential to create a common ground for improvement. It will be absolutely necessary to ensure alignment throughout the implementation too. Open and accessible guardrails Guardrails are the cornerstone of security requirements. Their nature and implementation are completely up to the needs of your organization and can be potentially very different from one company to the other (if starting from scratch, look no further than the OWASP Top10). What is most important, however, is that these guardrails are open to the ones that need them. A good example of this would be to centralize a common, security-approved library of open-source components that can be pulled from by any team. Keep users' accessibility and useability as a priority. Designing an AppSec program at scale requires asking “how can we build confidence and visibility with trusted tools in our ecosystem?”. For instance, control gates should never be implemented without considering a break-glass option (“what happens if the control is blocking in an emergency situation?”). State-of-the-art security is to have off-the-shelf secure solutions chosen by the developers, approved by security, and maintained by ops. This will be a big leap forward in preventing vulnerabilities from creeping into source code. It will bring security to the masses at a very low cost (low friction). But to truly scale application security, it would be silly not to use the software engineer's best ally: the continuous integration pipeline. Embed controls in the CI/CD AppSec testing across all development pipelines is the implementation step. If your organization has multiple development teams, it is very likely that different CI/CD pipelines configurations exist in parallel. They may use different tools, or simply define different steps in the build process. This is not a problem per se, but to scale application security, centralization and harmonization are needed. As illustrated in the following example CI/CD pipeline, you can have a lot of security control steps: secrets detection, SAST, artifact signing, access controls, but also container or Infrastructure as Code scanning (not shown in the example) (taken from the DevSecOps whitepaper) The idea is that you can progressively activate more and more control steps, fine-tune the existing ones and scale both horizontally and vertically your “AppSec infrastructure”, at one condition: you need to centralize metrics and controls in a stand-alone platform able to handle the load corresponding to your organization’s size. Security processes can only be automated when you have metrics and proper visibility across your development targets, otherwise, it is just more burden on the AppSec team's shoulders. In turn, metrics and visibility help drive change and provide the spark to ignite a cultural change within your organization. Security ownership shifts to every engineer involved in the delivery process, and each one is able to leverage its own deep (yet partial) knowledge of the system to support the effort. This unlocks a world of possibilities: most security flaws can be treated like regular tickets, rule sets can be optimized for each pipeline based on criticality, capabilities or regulatory compliance, and progress can be tracked (saved time, avoided vulnerabilities etc.). In simpler terms, security can finally move at the DevOps speed. Conclusion Security can’t scale if it’s siloed, and slowing down the development process is no longer an option in a world led by DevOps innovation. The design and implementation of security controls are bound to evolve. In this article, we’ve depicted a high-level overview of the steps to be considered to scale AppSec. This starts with establishing a set of security requirements that involve all the departments, in particular product-related ones. From there it becomes possible to design guardrails to make security truly accessible with a mix of hard and soft gates. By carefully selecting automated detection and remediation that provide visibility and control, you will be laying a solid foundation for a real model of shared responsibility for security. Finally, embedding checks in the CI/CD system can be rolled out in multiple phases to progressively scale your security operations. With automated feedback in place, you can start incrementally adjusting your policies. A centralized platform creates a common interface to facilitate the exchange between application security and developer teams while enforcing processes. It is a huge opportunity to automate and propagate best practices across teams. Developers are empowered to develop faster with more ownership. When security is rethought as a partnership between software-building stakeholders, a flywheel effect can take place: reduced friction leads to better communication and visibility, automating of more best practices, easing the work of each other while improving security with fewer defects. This is how application security will finally be able to scale through continuous improvement.

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