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Introduction The ever-changing landscape of cybersecurity, in which threats are becoming more sophisticated every day, organizations are looking to AI (AI) for bolstering their security. AI has for years been used in cybersecurity is currently being redefined to be agentsic AI and offers proactive, adaptive and context aware security. The article explores the potential of agentic AI to revolutionize security and focuses on use cases for AppSec and AI-powered automated vulnerability fixing. The rise of Agentic AI in Cybersecurity Agentic AI can be that refers to autonomous, goal-oriented robots that can discern their surroundings, and take decisions and perform actions that help them achieve their targets. Unlike traditional rule-based or reacting AI, agentic technology is able to evolve, learn, and operate with a degree of detachment. The autonomy they possess is displayed in AI agents in cybersecurity that are capable of continuously monitoring the network and find irregularities. Additionally, they can react in immediately to security threats, and threats without the interference of humans. Agentic AI's potential for cybersecurity is huge. ai security protection can be trained to identify patterns and correlates by leveraging machine-learning algorithms, along with large volumes of data. They can sift through the noise generated by many security events prioritizing the most important and providing insights for rapid response. Agentic AI systems have the ability to improve and learn their capabilities of detecting risks, while also being able to adapt themselves to cybercriminals constantly changing tactics. Agentic AI (Agentic AI) as well as Application Security Although agentic AI can be found in a variety of application across a variety of aspects of cybersecurity, its effect on the security of applications is significant. As organizations increasingly rely on interconnected, complex software systems, securing the security of these systems has been the top concern. AppSec strategies like regular vulnerability scanning as well as manual code reviews do not always keep up with modern application design cycles. Agentic AI is the new frontier. Through the integration of intelligent agents into the software development cycle (SDLC) businesses could transform their AppSec practice from proactive to. AI-powered software agents can constantly monitor the code repository and analyze each commit in order to identify vulnerabilities in security that could be exploited. They can leverage advanced techniques like static code analysis, automated testing, and machine learning to identify various issues, from common coding mistakes as well as subtle vulnerability to injection. AI is a unique feature of AppSec because it can be used to understand the context AI is unique to AppSec due to its ability to adjust to the specific context of every app. Agentic AI can develop an in-depth understanding of application structure, data flow, as well as attack routes by creating an exhaustive CPG (code property graph), a rich representation that shows the interrelations between code elements. The AI will be able to prioritize weaknesses based on their effect in the real world, and how they could be exploited, instead of relying solely on a standard severity score. The power of AI-powered Intelligent Fixing The concept of automatically fixing weaknesses is possibly the most interesting application of AI agent in AppSec. Human developers were traditionally in charge of manually looking over code in order to find the vulnerability, understand the problem, and finally implement the solution. It can take a long time, be error-prone and hold up the installation of vital security patches. The agentic AI game has changed. AI agents can detect and repair vulnerabilities on their own using CPG's extensive knowledge of codebase. They are able to analyze the code around the vulnerability to understand its intended function and then craft a solution that corrects the flaw but not introducing any new bugs. The implications of AI-powered automatic fix are significant. The amount of time between discovering a vulnerability before addressing the issue will be reduced significantly, closing the possibility of the attackers. It can alleviate the burden for development teams so that they can concentrate in the development of new features rather of wasting hours fixing security issues. Additionally, by automatizing the process of fixing, companies can ensure a consistent and reliable approach to vulnerabilities remediation, which reduces the chance of human error and oversights. Challenges and Considerations It is important to recognize the risks and challenges that accompany the adoption of AI agentics in AppSec as well as cybersecurity. In the area of accountability and trust is a crucial one. As AI agents grow more autonomous and capable acting and making decisions in their own way, organisations must establish clear guidelines and monitoring mechanisms to make sure that AI is operating within the bounds of acceptable behavior. AI follows the guidelines of acceptable behavior. It is important to implement robust testing and validating processes so that you can ensure the security and accuracy of AI produced changes. Another concern is the possibility of adversarial attack against AI. The attackers may attempt to alter data or exploit AI models' weaknesses, as agentic AI systems are more common within cyber security. It is essential to employ secure AI methods like adversarial-learning and model hardening. In addition, the efficiency of agentic AI used in AppSec is dependent upon the completeness and accuracy of the code property graph. The process of creating and maintaining an exact CPG requires a significant spending on static analysis tools, dynamic testing frameworks, as well as data integration pipelines. Companies also have to make sure that their CPGs keep up with the constant changes occurring in the codebases and evolving threat areas. The Future of Agentic AI in Cybersecurity The potential of artificial intelligence in cybersecurity is exceptionally promising, despite the many challenges. The future will be even advanced and more sophisticated autonomous systems to recognize cyber threats, react to them, and diminish their effects with unprecedented efficiency and accuracy as AI technology continues to progress. In the realm of 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 reliable, secure, and resilient applications. Additionally, the integration of AI-based agent systems into the broader cybersecurity ecosystem can open up new possibilities to collaborate and coordinate various security tools and processes. Imagine a world in which agents are self-sufficient and operate in the areas of network monitoring, incident responses as well as threats security and intelligence. They would share insights as well as coordinate their actions and offer proactive cybersecurity. It is vital that organisations accept the use of AI agents as we progress, while being aware of the ethical and social impacts. Through fostering a culture that promotes accountable AI development, transparency, and accountability, it is possible to make the most of the potential of agentic AI to build a more robust and secure digital future. The conclusion of the article can be summarized as: Agentic AI is an exciting advancement in the world of cybersecurity. It is a brand new approach to recognize, avoid the spread of cyber-attacks, and reduce their impact. The ability of an autonomous agent particularly in the field of automated vulnerability fixing and application security, can enable organizations to transform their security practices, shifting from a reactive strategy to a proactive approach, automating procedures moving from a generic approach to contextually-aware. There are many challenges ahead, but the potential benefits of agentic AI can't be ignored. not consider. As we continue to push the limits of AI for cybersecurity, it is essential to consider this technology with the mindset of constant adapting, learning and accountable innovation. This way we can unleash the full power of agentic AI to safeguard our digital assets, secure our organizations, and build better security for all.