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Introduction Artificial Intelligence (AI) which is part of the continuously evolving world of cyber security it is now being utilized by organizations to strengthen their defenses. As security threats grow more sophisticated, companies are increasingly turning towards AI. Although AI has been part of cybersecurity tools since a long time but the advent of agentic AI can signal a new era in intelligent, flexible, and contextually sensitive security solutions. This article examines the possibilities of agentic AI to revolutionize security and focuses on use cases to AppSec and AI-powered automated vulnerability fix. Cybersecurity is the rise of artificial intelligence (AI) that is agent-based Agentic AI refers specifically to self-contained, goal-oriented systems which are able to perceive their surroundings take decisions, decide, and take actions to achieve particular goals. Contrary to conventional rule-based, reactive AI, these systems possess the ability to evolve, learn, and work with a degree of autonomy. In the context of cybersecurity, the autonomy translates into AI agents that can constantly monitor networks, spot suspicious behavior, and address security threats immediately, with no any human involvement. Agentic AI is a huge opportunity in the area of cybersecurity. With the help of machine-learning algorithms as well as vast quantities of data, these intelligent agents can detect patterns and correlations that analysts would miss. Intelligent agents are able to sort through the noise of numerous security breaches and prioritize the ones that are most significant and offering information for rapid response. Agentic AI systems are able to develop and enhance their abilities to detect security threats and changing their strategies to match cybercriminals changing strategies. Agentic AI (Agentic AI) and Application Security Although agentic AI can be found in a variety of applications across various aspects of cybersecurity, its influence in the area of application security is noteworthy. Securing applications is a priority for businesses that are reliant ever more heavily on interconnected, complex software systems. Standard AppSec approaches, such as manual code review and regular vulnerability tests, struggle to keep up with the rapidly-growing development cycle and attack surface of modern applications. Agentic AI can be the solution. By integrating intelligent agents into the lifecycle of software development (SDLC) businesses can change their AppSec practices from reactive to proactive. The AI-powered agents will continuously check code repositories, and examine every commit for vulnerabilities and security issues. They may employ advanced methods like static code analysis test-driven testing and machine learning, to spot the various vulnerabilities, from common coding mistakes to subtle injection vulnerabilities. What sets agentic AI different from the AppSec area is its capacity to recognize and adapt to the particular situation of every app. Agentic AI is able to develop an understanding of the application's structure, data flow, and attack paths by building a comprehensive CPG (code property graph) which is a detailed representation that reveals the relationship between various code components. The AI will be able to prioritize weaknesses based on their effect on the real world and also the ways they can be exploited rather than relying on a generic severity rating. Artificial Intelligence-powered Automatic Fixing: The Power of AI The idea of automating the fix for weaknesses is possibly the most intriguing application for AI agent technology in AppSec. When a flaw has been identified, it is on the human developer to examine the code, identify the vulnerability, and apply fix. It can take a long time, can be prone to error and hold up the installation of vital security patches. The game has changed with the advent of agentic AI. Utilizing the extensive comprehension of the codebase offered by CPG, AI agents can not just detect weaknesses and create context-aware and non-breaking fixes. These intelligent agents can analyze the code that is causing the issue and understand the purpose of the vulnerability and then design a fix which addresses the security issue while not introducing bugs, or damaging existing functionality. The AI-powered automatic fixing process has significant effects. The amount of time between finding a flaw and fixing the problem can be greatly reduced, shutting a window of opportunity to attackers. This can relieve the development team from the necessity to spend countless hours on finding security vulnerabilities. In their place, the team can focus on developing new capabilities. Moreover, by automating the fixing process, organizations will be able to ensure consistency and reliable method of vulnerabilities remediation, which reduces the risk of human errors and errors. What are the challenges and the considerations? It is vital to acknowledge the risks and challenges associated with the use of AI agentics in AppSec as well as cybersecurity. It is important to consider accountability and trust is a crucial one. As AI agents become more autonomous and capable of making decisions and taking actions on their own, organizations must establish clear guidelines as well as oversight systems to make sure that the AI follows the guidelines of acceptable behavior. It is crucial to put in place solid testing and validation procedures in order to ensure the safety and correctness of AI developed corrections. Another issue is the potential for adversarial attacks against AI systems themselves. When agent-based AI techniques become more widespread in the field of cybersecurity, hackers could try to exploit flaws in the AI models, or alter the data upon which they are trained. This underscores the importance of security-conscious AI practice in development, including techniques like adversarial training and modeling hardening. In addition, the efficiency of the agentic AI in AppSec depends on the integrity and reliability of the code property graph. To construct and keep an precise CPG You will have to spend money on devices like static analysis, testing frameworks, and pipelines for integration. It is also essential that organizations ensure their CPGs constantly updated to take into account changes in the source code and changing threat landscapes. Cybersecurity Future of artificial intelligence The future of autonomous artificial intelligence in cybersecurity appears promising, despite the many problems. Expect even better and advanced autonomous agents to detect cyber-attacks, react to these threats, and limit the impact of these threats with unparalleled agility and speed as AI technology advances. With ai-powered app security to AppSec, agentic AI has the potential to change the process of creating and secure software, enabling enterprises to develop more powerful safe, durable, and reliable apps. The integration of AI agentics to the cybersecurity industry opens up exciting possibilities for collaboration and coordination between security tools and processes. Imagine a world in which agents operate autonomously and are able to work in the areas of network monitoring, incident response, as well as threat information and vulnerability monitoring. They would share insights that they have, collaborate on actions, and help to provide a proactive defense against cyberattacks. It is vital that organisations accept the use of AI agents as we develop, and be mindful of the ethical and social implications. If we can foster a culture of accountable AI advancement, transparency and accountability, we are able to make the most of the potential of agentic AI to create a more robust and secure digital future. Conclusion In today's rapidly changing world of cybersecurity, the advent of agentic AI represents a paradigm shift in the method we use to approach the detection, prevention, and elimination of cyber-related threats. By leveraging the power of autonomous agents, particularly in the realm of app security, and automated fix for vulnerabilities, companies can shift their security strategies from reactive to proactive from manual to automated, as well as from general to context sensitive. Agentic AI is not without its challenges but the benefits are sufficient to not overlook. When we are pushing the limits of AI for cybersecurity, it's crucial to remain in a state to keep learning and adapting of responsible and innovative ideas. In this way it will allow us to tap into the full potential of artificial intelligence to guard our digital assets, protect the organizations we work for, and provide better security for all.