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Introduction In the ever-evolving landscape of cybersecurity, as threats grow more sophisticated by the day, enterprises are relying on AI (AI) to enhance their defenses. Although AI is a component of cybersecurity tools for some time, the emergence of agentic AI can signal a new age of innovative, adaptable and contextually-aware security tools. This article examines the transformative potential of agentic AI by focusing on its applications in application security (AppSec) and the ground-breaking idea of automated fix for vulnerabilities. Cybersecurity The rise of artificial intelligence (AI) that is agent-based Agentic AI is a term which refers to goal-oriented autonomous robots that are able to perceive their surroundings, take decisions and perform actions to achieve specific desired goals. Agentic AI differs from traditional reactive or rule-based AI, in that it has the ability to adjust and learn to the environment it is in, and also operate on its own. This independence is evident in AI agents in cybersecurity that have the ability to constantly monitor the networks and spot any anomalies. They also can respond instantly to any threat with no human intervention. Agentic AI's potential in cybersecurity is enormous. Agents with intelligence are able to identify patterns and correlates using machine learning algorithms and large amounts of data. They can sort through the chaos of many security events, prioritizing the most crucial incidents, and provide actionable information for rapid intervention. Agentic AI systems can be trained to learn and improve their ability to recognize threats, as well as changing their strategies to match cybercriminals and their ever-changing tactics. Agentic AI (Agentic AI) as well as Application Security Agentic AI is a powerful instrument that is used for a variety of aspects related to cyber security. But, the impact it can have on the security of applications is particularly significant. As organizations increasingly rely on highly interconnected and complex software systems, securing the security of these systems has been a top priority. AppSec tools like routine vulnerability scanning and manual code review can often not keep up with rapid developments. In the realm of agentic AI, you can enter. By integrating intelligent agents into the lifecycle of software development (SDLC) businesses can change their AppSec procedures from reactive proactive. AI-powered agents are able to continuously monitor code repositories and examine each commit in order to spot weaknesses in security. They may employ advanced methods such as static analysis of code, dynamic testing, as well as machine learning to find a wide range of issues that range from simple coding errors as well as subtle vulnerability to injection. The thing that sets agentic AI distinct from other AIs in the AppSec sector is its ability to understand and adapt to the unique environment of every application. With the help of a thorough CPG – a graph of the property code (CPG) – a rich diagram of the codebase which is able to identify the connections between different components of code – agentsic AI has the ability to develop an extensive understanding of the application's structure in terms of data flows, its structure, and attack pathways. The AI is able to rank weaknesses based on their effect in real life and how they could be exploited rather than relying upon a universal severity rating. The Power of AI-Powered Automated Fixing The idea of automating the fix for vulnerabilities is perhaps one of the greatest applications for AI agent AppSec. Humans have historically been responsible for manually reviewing the code to discover the vulnerabilities, learn about the issue, and implement the corrective measures. This could take quite a long time, can be prone to error and delay the deployment of critical security patches. Through agentic AI, the game changes. AI agents are able to identify and fix vulnerabilities automatically through the use of CPG's vast understanding of the codebase. The intelligent agents will analyze the code surrounding the vulnerability as well as understand the functionality intended as well as design a fix that addresses the security flaw without adding new bugs or breaking existing features. AI-powered, automated fixation has huge consequences. It is estimated that the time between finding a flaw and fixing the problem can be reduced significantly, closing a window of opportunity to hackers. It can alleviate the burden on the development team, allowing them to focus on creating new features instead then wasting time fixing security issues. Furthermore, through automatizing fixing processes, organisations will be able to ensure consistency and reliable method of vulnerabilities remediation, which reduces the risk of human errors and mistakes. Questions and Challenges Though the scope of agentsic AI in cybersecurity and AppSec is vast however, it is vital to be aware of the risks and concerns that accompany its use. It is important to consider accountability as well as trust is an important issue. Organisations need to establish clear guidelines to ensure that AI is acting within the acceptable parameters since AI agents grow autonomous and begin to make decision on their own. It is essential to establish solid testing and validation procedures so that you can ensure the quality and security of AI created corrections. Another issue is the risk of attackers against the AI system itself. The attackers may attempt to alter the data, or exploit AI models' weaknesses, as agentic AI models are increasingly used in cyber security. It is important to use safe AI techniques like adversarial learning as well as model hardening. The quality and completeness the code property diagram is also a major factor in the success of AppSec's agentic AI. To build and keep an exact CPG it is necessary to invest in techniques like static analysis, testing frameworks, and pipelines for integration. Organizations must also ensure that their CPGs are updated to reflect changes that take place in their codebases, as well as the changing threat areas. Cybersecurity The future of artificial intelligence In spite of the difficulties however, the future of AI in cybersecurity looks incredibly hopeful. We can expect even advanced and more sophisticated autonomous agents to detect cyber security threats, react to them, and minimize the damage they cause with incredible speed and precision as AI technology advances. Agentic AI within AppSec can revolutionize the way that software is designed and developed which will allow organizations to design more robust and secure apps. Moreover, the integration in the cybersecurity landscape provides exciting possibilities for collaboration and coordination between different security processes and tools. Imagine a scenario where autonomous agents are able to work in tandem in the areas of network monitoring, incident response, threat intelligence and vulnerability management. They share insights as well as coordinating their actions to create a comprehensive, proactive protection against cyber attacks. ai in devsecops is essential that companies embrace agentic AI as we develop, and be mindful of its ethical and social implications. It is possible to harness the power of AI agentics to create an incredibly secure, robust, and reliable digital future by encouraging a sustainable culture in AI creation. Conclusion In the fast-changing world in cybersecurity, agentic AI represents a paradigm change in the way we think about the detection, prevention, and mitigation of cyber security threats. With the help of autonomous agents, especially in the realm of application security and automatic security fixes, businesses can change their security strategy by shifting from reactive to proactive, by moving away from manual processes to automated ones, and also from being generic to context conscious. Although there are still challenges, the benefits that could be gained from agentic AI can't be ignored. leave out. When we are pushing the limits of AI when it comes to cybersecurity, it's vital to be aware of continuous learning, adaptation and wise innovations. This will allow us to unlock the power of artificial intelligence to protect companies and digital assets.