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This is a short outline of the subject: Artificial Intelligence (AI) is a key component in the ever-changing landscape of cyber security it is now being utilized by companies to enhance their security. As threats become increasingly complex, security professionals are turning increasingly towards AI. Although AI has been a part of the cybersecurity toolkit since the beginning of time and has been around for a while, the advent of agentsic AI has ushered in a brand revolution in innovative, adaptable and contextually-aware security tools. This article delves into the potential for transformational benefits of agentic AI and focuses specifically on its use in applications security (AppSec) and the pioneering concept of automatic vulnerability-fixing. The Rise of Agentic AI in Cybersecurity Agentic AI is a term applied to autonomous, goal-oriented robots which are able see their surroundings, make decision-making and take actions to achieve specific desired goals. Unlike traditional rule-based or reactive AI systems, agentic AI machines are able to adapt and learn and work with a degree of autonomy. This independence is evident in AI agents in cybersecurity that can continuously monitor the networks and spot abnormalities. They also can respond real-time to threats in a non-human manner. Agentic AI has immense potential in the field of cybersecurity. Agents with intelligence are able to identify patterns and correlates using machine learning algorithms as well as large quantities of data. They can sift through the chaos of many security-related events, and prioritize the most crucial incidents, and providing a measurable insight for quick response. Agentic AI systems can be trained to grow and develop their ability to recognize risks, while also changing their strategies to match cybercriminals changing strategies. Agentic AI (Agentic AI) and Application Security Agentic AI is an effective instrument that is used for a variety of aspects related to cyber security. However, the impact it has on application-level security is noteworthy. Security of applications is an important concern for businesses that are reliant increasing on interconnected, complex software platforms. AppSec tools like routine vulnerability testing as well as manual code reviews are often unable to keep current with the latest application development cycles. The answer is Agentic AI. Through the integration of intelligent agents in the lifecycle of software development (SDLC) organisations could transform their AppSec practices from reactive to proactive. AI-powered systems can continually monitor repositories of code and analyze each commit to find weaknesses in security. They can employ advanced techniques such as static code analysis as well as dynamic testing to find many kinds of issues that range from simple code errors to subtle injection flaws. The thing that sets agentic AI out in the AppSec field is its capability to understand and adapt to the distinct situation of every app. Agentic AI has the ability to create an extensive understanding of application design, data flow as well as attack routes by creating an extensive CPG (code property graph) that is a complex representation that reveals the relationship between code elements. https://sites.google.com/view/howtouseaiinapplicationsd8e/ai-copilots-that-write-secure-code allows the AI to prioritize security holes based on their impact and exploitability, rather than relying on generic severity rating. The power of AI-powered Autonomous Fixing Automatedly fixing vulnerabilities is perhaps the most intriguing application for AI agent within AppSec. Traditionally, once a vulnerability has been discovered, it falls on humans to review the code, understand the flaw, and then apply an appropriate fix. The process is time-consuming as well as error-prone. It often can lead to delays in the implementation of essential security patches. The game has changed with the advent of agentic AI. Through the use of the in-depth comprehension of the codebase offered by CPG, AI agents can not just identify weaknesses, and create context-aware not-breaking solutions automatically. They can analyze the code that is causing the issue and understand the purpose of it and then craft a solution which fixes the issue while making sure that they do not introduce new problems. AI-powered automated fixing has profound effects. It will significantly cut down the amount of time that is spent between finding vulnerabilities and repair, cutting down the opportunity for attackers. This will relieve the developers team from the necessity to dedicate countless hours remediating security concerns. They could work on creating new features. Automating the process of fixing weaknesses will allow organizations to be sure that they are using a reliable and consistent method, which reduces the chance of human errors and oversight. What are the obstacles and considerations? Though ai security setup of agentsic AI for cybersecurity and AppSec is vast It is crucial to understand the risks and concerns that accompany the adoption of this technology. The most important concern is that of confidence and accountability. The organizations must set clear rules to make sure that AI is acting within the acceptable parameters since AI agents gain autonomy and can take independent decisions. It is vital to have solid testing and validation procedures to guarantee the safety and correctness of AI developed solutions. A second challenge is the potential for adversarial attack against AI. As agentic AI techniques become more widespread in the field of cybersecurity, hackers could try to exploit flaws in AI models or manipulate the data from which they're taught. It is imperative to adopt secured AI practices such as adversarial learning as well as model hardening. In addition, the efficiency of agentic AI for agentic AI in AppSec is heavily dependent on the quality and completeness of the graph for property code. To construct and maintain an exact CPG it is necessary to spend money on devices like static analysis, test frameworks, as well as pipelines for integration. Organisations also need to ensure they are ensuring that their CPGs correspond to the modifications that occur in codebases and shifting security environments. Cybersecurity: The future of AI-agents The future of AI-based agentic intelligence in cybersecurity appears positive, in spite of the numerous problems. As AI technologies continue to advance it is possible to get even more sophisticated and powerful autonomous systems which can recognize, react to, and combat cybersecurity threats at a rapid pace and precision. For AppSec agents, AI-based agentic security has an opportunity to completely change how we create and protect software. It will allow businesses to build more durable as well as secure software. The introduction of AI agentics to the cybersecurity industry offers exciting opportunities for coordination and collaboration between security processes and tools. Imagine a world where autonomous agents collaborate seamlessly through network monitoring, event response, threat intelligence and vulnerability management. They share insights as well as coordinating their actions to create an integrated, proactive defence against cyber attacks. In the future as we move forward, it's essential for businesses to be open to the possibilities of agentic AI while also being mindful of the moral implications and social consequences of autonomous AI systems. The power of AI agentics to create security, resilience digital world by creating a responsible and ethical culture in AI development. The conclusion of the article is as follows: Agentic AI is a revolutionary advancement in cybersecurity. It is a brand new paradigm for the way we discover, detect the spread of cyber-attacks, and reduce their impact. By leveraging the power of autonomous agents, especially in the realm of application security and automatic fix for vulnerabilities, companies can shift their security strategies from reactive to proactive from manual to automated, and from generic to contextually conscious. Agentic AI has many challenges, yet the rewards are too great to ignore. While we push AI's boundaries in the field of cybersecurity, it's vital to be aware to keep learning and adapting, and responsible innovations. It is then possible to unleash the capabilities of agentic artificial intelligence in order to safeguard the digital assets of organizations and their owners.