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Introduction In the constantly evolving world of cybersecurity, in which threats become more sophisticated each day, enterprises are relying on AI (AI) for bolstering their defenses. While AI has been a part of the cybersecurity toolkit for some time but the advent of agentic AI will usher in a new age of intelligent, flexible, and contextually-aware security tools. This article focuses on the revolutionary potential of AI by focusing on its application in the field of application security (AppSec) and the groundbreaking concept of automatic security fixing. https://www.linkedin.com/posts/qwiet_gartner-appsec-qwietai-activity-7203450652671258625-Nrz0 of Agentic AI in Cybersecurity Agentic AI can be which refers to goal-oriented autonomous robots that are able to see their surroundings, make action that help them achieve their goals. As opposed to the traditional rules-based or reacting AI, agentic machines are able to learn, adapt, and work with a degree of independence. In the context of cybersecurity, that autonomy is translated into AI agents that continually monitor networks, identify suspicious behavior, and address attacks in real-time without any human involvement. Agentic AI is a huge opportunity in the field of cybersecurity. Intelligent agents are able to identify patterns and correlates with machine-learning algorithms along with large volumes of data. These intelligent agents can sort through the noise of a multitude of security incidents, prioritizing those that are most significant and offering information for quick responses. Furthermore, agentsic AI systems can gain knowledge from every incident, improving their detection of threats as well as adapting to changing strategies of cybercriminals. Agentic AI and Application Security Agentic AI is a broad field of application in various areas of cybersecurity, its influence on security for applications is important. Security of applications is an important concern for organizations that rely increasing on complex, interconnected software platforms. The traditional AppSec approaches, such as manual code reviews or periodic vulnerability scans, often struggle to keep up with the fast-paced development process and growing threat surface that modern software applications. Agentic AI could be the answer. Incorporating intelligent agents into the software development cycle (SDLC), organisations can change their AppSec process from being reactive to proactive. The AI-powered agents will continuously monitor code repositories, analyzing every code change for vulnerability and security issues. They employ sophisticated methods like static code analysis test-driven testing and machine learning, to spot numerous issues that range from simple coding errors to subtle vulnerabilities in injection. The thing that sets the agentic AI distinct from other AIs in the AppSec domain is its ability to understand and adapt to the distinct circumstances of each app. Agentic AI is capable of developing an in-depth understanding of application structure, data flow and the attack path by developing the complete CPG (code property graph), a rich representation that reveals the relationship among code elements. agentic automatic ai security fixes is able to rank vulnerability based upon their severity in the real world, and ways to exploit them, instead of relying solely on a generic severity rating. Artificial Intelligence-powered Automatic Fixing the Power of AI Perhaps the most interesting application of AI that is agentic AI within AppSec is automated vulnerability fix. Human programmers have been traditionally accountable for reviewing manually the code to discover the flaw, analyze the issue, and implement the fix. The process is time-consuming in addition to error-prone and frequently causes delays in the deployment of essential security patches. Agentic AI is a game changer. situation is different. AI agents are able to detect and repair vulnerabilities on their own thanks to CPG's in-depth expertise in the field of codebase. The intelligent agents will analyze the code that is causing the issue as well as understand the functionality intended as well as design a fix that fixes the security flaw without introducing new bugs or affecting existing functions. The implications of AI-powered automatic fixing are profound. It will significantly cut down the time between vulnerability discovery and its remediation, thus eliminating the opportunities to attack. This can relieve the development group of having to invest a lot of time fixing security problems. They could focus on developing new capabilities. Moreover, by automating fixing processes, organisations are able to guarantee a consistent and reliable method of vulnerability remediation, reducing the risk of human errors and oversights. What are ai security measurements and the considerations? Although the possibilities of using agentic AI in cybersecurity and AppSec is huge however, it is vital to acknowledge the challenges and concerns that accompany the adoption of this technology. The issue of accountability and trust is an essential issue. The organizations must set clear rules to make sure that AI acts within acceptable boundaries in the event that AI agents develop autonomy and can take decision on their own. This means implementing rigorous verification and testing procedures that verify the correctness and safety of AI-generated solutions. Another challenge lies in the potential for adversarial attacks against AI systems themselves. In the future, as agentic AI systems are becoming more popular in the world of cybersecurity, adversaries could be looking to exploit vulnerabilities in AI models or to alter the data on which they're based. This underscores the importance of secure AI methods of development, which include techniques like adversarial training and the hardening of models. In addition, the efficiency of the agentic AI for agentic AI in AppSec depends on the accuracy and quality of the property graphs for code. Building and maintaining an exact CPG is a major spending on static analysis tools and frameworks for dynamic testing, and pipelines for data integration. Organizations must also ensure that they ensure that their CPGs remain up-to-date so that they reflect the changes to the codebase and ever-changing threats. The future of Agentic AI in Cybersecurity The future of AI-based agentic intelligence in cybersecurity is exceptionally optimistic, despite its many obstacles. As AI techniques continue to evolve and become more advanced, we could be able to see more advanced and efficient autonomous agents capable of detecting, responding to and counter cyber attacks with incredible speed and accuracy. In the realm of AppSec, agentic AI has the potential to change the process of creating and secure software. This could allow organizations to deliver more robust as well as secure apps. The introduction of AI agentics to the cybersecurity industry offers exciting opportunities for coordination and collaboration between security tools and processes. Imagine a world w here autonomous agents work seamlessly across network monitoring, incident response, threat intelligence, and vulnerability management, sharing information and co-ordinating actions for an all-encompassing, proactive defense against cyber threats. It is crucial that businesses adopt agentic AI in the course of develop, and be mindful of its social and ethical implications. Through fostering a culture that promotes accountability, responsible AI creation, transparency and accountability, we will be able to harness the power of agentic AI to build a more robust and secure digital future. Conclusion In today's rapidly changing world of cybersecurity, agentic AI represents a paradigm transformation in the approach we take to the prevention, detection, and elimination of cyber-related threats. The capabilities of an autonomous agent specifically in the areas of automatic vulnerability fix and application security, could assist organizations in transforming their security strategies, changing from a reactive strategy to a proactive one, automating processes that are generic and becoming contextually aware. Although there are still challenges, agents' potential advantages AI are too significant to not consider. When we are pushing the limits of AI when it comes to cybersecurity, it's important to keep a mind-set that is constantly learning, adapting, and responsible innovations. This will allow us to unlock the full potential of AI agentic intelligence for protecting businesses and assets.