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Introduction The ever-changing landscape of cybersecurity, as threats get more sophisticated day by day, organizations are looking to AI (AI) to strengthen their defenses. Although AI has been a part of cybersecurity tools since the beginning of time however, the rise of agentic AI will usher in a fresh era of innovative, adaptable and contextually aware security solutions. This article examines the revolutionary potential of AI by focusing on its applications in application security (AppSec) as well as the revolutionary concept of automatic security fixing. Cybersecurity A rise in artificial intelligence (AI) that is agent-based Agentic AI is a term used to describe self-contained, goal-oriented systems which recognize their environment take decisions, decide, and take actions to achieve certain goals. In contrast to traditional rules-based and reactive AI, these systems are able to evolve, learn, and operate with a degree that is independent. The autonomy they possess is displayed in AI security agents that have the ability to constantly monitor systems and identify abnormalities. They are also able to respond in immediately to security threats, and threats without the interference of humans. The potential of agentic AI in cybersecurity is immense. With the help of machine-learning algorithms and huge amounts of information, these smart agents can identify patterns and correlations which human analysts may miss. Intelligent agents are able to sort through the noise of numerous security breaches, prioritizing those that are most important and providing insights to help with rapid responses. Additionally, AI agents can gain knowledge from every incident, improving their detection of threats and adapting to constantly changing strategies of cybercriminals. Agentic AI (Agentic AI) as well as Application Security Agentic AI is an effective technology that is able to be employed in many aspects of cyber security. The impact the tool has on security at an application level is noteworthy. As organizations increasingly rely on highly interconnected and complex software systems, safeguarding the security of these systems has been the top concern. The traditional AppSec methods, like manual code reviews, as well as periodic vulnerability assessments, can be difficult to keep up with fast-paced development process and growing vulnerability of today's applications. Agentic AI could be the answer. Through the integration of intelligent agents into the software development cycle (SDLC), organisations are able to transform their AppSec practices from reactive to proactive. AI-powered agents can constantly monitor the code repository and evaluate each change in order to identify vulnerabilities in security that could be exploited. These AI-powered agents are able to use sophisticated techniques like static code analysis as well as dynamic testing to detect many kinds of issues that range from simple code errors to more subtle flaws in injection. What separates agentic AI apart in the AppSec sector is its ability to comprehend and adjust to the particular circumstances of each app. Agentic AI is capable of developing an extensive understanding of application structure, data flow and the attack path by developing the complete CPG (code property graph) that is a complex representation that reveals the relationship between the code components. The AI can prioritize the vulnerability based upon their severity in the real world, and what they might be able to do and not relying on a general severity rating. AI-Powered Automated Fixing A.I.-Powered Autofixing: The Power of AI The notion of automatically repairing weaknesses is possibly one of the greatest applications for AI agent AppSec. Humans have historically been required to manually review codes to determine vulnerabilities, comprehend it and then apply the fix. This process can be time-consuming with a high probability of error, which often causes delays in the deployment of critical security patches. With agentic AI, the game changes. AI agents are able to identify and fix vulnerabilities automatically using CPG's extensive understanding of the codebase. They can analyse all the relevant code in order to comprehend its function and then craft a solution that fixes the flaw while being careful not to introduce any additional problems. AI-powered, automated fixation has huge consequences. It will significantly cut down the amount of time that is spent between finding vulnerabilities and remediation, making it harder for cybercriminals. It can alleviate the burden on the development team and allow them to concentrate on building new features rather and wasting their time solving security vulnerabilities. Furthermore, through automatizing the repair process, businesses can guarantee a uniform and reliable method of vulnerabilities remediation, which reduces the possibility of human mistakes and errors. Challenges and Considerations It is crucial to be aware of the risks and challenges which accompany the introduction of AI agents in AppSec and cybersecurity. In the area of accountability as well as trust is an important one. Organisations need to establish clear guidelines for ensuring that AI behaves within acceptable boundaries when AI agents become autonomous and are able to take decision on their own. This includes the implementation of robust tests and validation procedures to confirm the accuracy and security of AI-generated changes. A second challenge is the potential for adversarial attack against AI. An attacker could try manipulating information or attack AI weakness in models since agentic AI systems are more common for cyber security. It is imperative to adopt secured AI practices such as adversarial-learning and model hardening. The accuracy and quality of the property diagram for code is also a major factor to the effectiveness of AppSec's agentic AI. To construct and maintain an accurate CPG, you will need to purchase tools such as static analysis, testing frameworks and integration pipelines. Companies must ensure that they ensure that their CPGs remain up-to-date to reflect changes in the codebase and evolving threats. Cybersecurity The future of AI agentic The future of autonomous artificial intelligence for cybersecurity is very hopeful, despite all the issues. The future will be even more capable and sophisticated self-aware agents to spot cyber security threats, react to them, and diminish the impact of these threats with unparalleled speed and precision as AI technology develops. In the realm of AppSec Agentic AI holds the potential to revolutionize the process of creating and secure software. https://sites.google.com/view/howtouseaiinapplicationsd8e/ai-in-cyber-security will enable businesses to build more durable reliable, secure, and resilient applications. Furthermore, the incorporation of artificial intelligence into the wider cybersecurity ecosystem opens up exciting possibilities of collaboration and coordination between different security processes and tools. Imagine a world in which agents operate autonomously and are able to work on network monitoring and response as well as threat intelligence and vulnerability management. They could share information to coordinate actions, as well as give proactive cyber security. It is essential that companies accept the use of AI agents as we progress, while being aware of its ethical and social impact. Through fostering a culture that promotes ethical AI development, transparency, and accountability, we can harness the power of agentic AI in order to construct a secure and resilient digital future. Conclusion In today's rapidly changing world of cybersecurity, the advent of agentic AI is a fundamental change in the way we think about the identification, prevention and mitigation of cyber threats. Through the use of autonomous agents, particularly in the realm of application security and automatic vulnerability fixing, organizations can transform their security posture from reactive to proactive from manual to automated, as well as from general to context cognizant. Agentic AI is not without its challenges however the advantages are more than we can ignore. As we continue pushing the boundaries of AI in cybersecurity, it is essential to consider this technology with an attitude of continual training, adapting and accountable innovation. If we do this we will be able to unlock the potential of agentic AI to safeguard our digital assets, secure the organizations we work for, and provide a more secure future for all.