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The following article is an overview of the subject: In the ever-evolving landscape of cybersecurity, where threats get more sophisticated day by day, businesses are turning to artificial intelligence (AI) to bolster their defenses. AI has for years been used in cybersecurity is now being re-imagined as an agentic AI and offers active, adaptable and fully aware security. This article delves into the transformative potential of agentic AI with a focus specifically on its use in applications security (AppSec) and the pioneering concept of AI-powered automatic security fixing. The Rise of Agentic AI in Cybersecurity Agentic AI is the term applied to autonomous, goal-oriented robots that can detect their environment, take decisions and perform actions for the purpose of achieving specific goals. Agentic AI is distinct from the traditional rule-based or reactive AI, in that it has the ability to change and adapt to the environment it is in, as well as operate independently. This autonomy is translated into AI agents working in cybersecurity. They can continuously monitor the networks and spot irregularities. They are also able to respond in real-time to threats and threats without the interference of humans. The application of AI agents in cybersecurity is vast. The intelligent agents can be trained to recognize patterns and correlatives through machine-learning algorithms as well as large quantities of data. Intelligent agents are able to sort through the noise of several security-related incidents, prioritizing those that are most significant and offering information that can help in rapid reaction. Agentic AI systems can be trained to develop and enhance the ability of their systems to identify dangers, and being able to adapt themselves to cybercriminals changing strategies. 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 impact in the area of application security is noteworthy. Secure applications are a top priority for businesses that are reliant increasingly on interconnected, complex software platforms. AppSec techniques such as periodic vulnerability analysis and manual code review can often not keep up with rapid development cycles. Enter agentic AI. Incorporating ai security frameworks into the lifecycle of software development (SDLC) businesses could transform their AppSec procedures from reactive proactive. The AI-powered agents will continuously check code repositories, and examine every code change for vulnerability as well as security vulnerabilities. These agents can use advanced techniques like static code analysis as well as dynamic testing, which can detect numerous issues, from simple coding errors or subtle injection flaws. https://sites.google.com/view/howtouseaiinapplicationsd8e/gen-ai-in-cybersecurity is unique in AppSec due to its ability to adjust and understand the context of each and every application. Agentic AI is capable of developing an in-depth understanding of application structure, data flow, as well as attack routes by creating an extensive CPG (code property graph), a rich representation of the connections between code elements. This allows the AI to determine the most vulnerable vulnerability based upon their real-world potential impact and vulnerability, instead of relying on general severity scores. The Power of AI-Powered Automated Fixing The most intriguing application of agentic AI within AppSec is automated vulnerability fix. Human developers were traditionally required to manually review the code to discover the vulnerability, understand the problem, and finally implement the solution. It could take a considerable period of time, and be prone to errors. It can also hold up the installation of vital security patches. The agentic AI game is changed. AI agents are able to identify and fix vulnerabilities automatically by leveraging CPG's deep knowledge of codebase. They are able to analyze all the relevant code and understand the purpose of it before implementing a solution that fixes the flaw while creating no new security issues. The consequences of AI-powered automated fix are significant. It can significantly reduce the time between vulnerability discovery and resolution, thereby cutting down the opportunity for hackers. It can also relieve the development team of the need to invest a lot of time remediating security concerns. In their place, the team could be able to concentrate on the development of new features. Automating the process of fixing weaknesses can help organizations ensure they are using a reliable and consistent method that reduces the risk for human error and oversight. What are the main challenges and issues to be considered? It is crucial to be aware of the threats and risks in the process of implementing AI agents in AppSec as well as cybersecurity. It is important to consider accountability and trust is an essential one. The organizations must set clear rules for ensuring that AI behaves within acceptable boundaries since AI agents grow autonomous and become capable of taking the decisions for themselves. This means implementing rigorous testing and validation processes to verify the correctness and safety of AI-generated fix. ai security design patterns lies in the threat of attacks against the AI system itself. Hackers could attempt to modify information or take advantage of AI models' weaknesses, as agents of AI models are increasingly used in cyber security. This highlights the need for secured AI practice in development, including methods such as adversarial-based training and the hardening of models. The accuracy and quality of the diagram of code properties can be a significant factor in the performance of AppSec's AI. To build and keep an exact CPG the organization will have to acquire devices like static analysis, testing frameworks, and pipelines for integration. Organizations must also ensure that their CPGs constantly updated to reflect changes in the security codebase as well as evolving threat landscapes. Cybersecurity Future of agentic AI Despite the challenges and challenges, the future for agentic cyber security AI is promising. As Continuous security continue to advance it is possible to see even more sophisticated and resilient autonomous agents that can detect, respond to, and mitigate cybersecurity threats at a rapid pace and accuracy. In the realm of AppSec Agentic AI holds the potential to transform how we design and protect software. It will allow enterprises to develop more powerful, resilient, and secure software. The integration of AI agentics into the cybersecurity ecosystem opens up exciting possibilities to collaborate and coordinate security processes and tools. Imagine a world in which agents are autonomous and work throughout network monitoring and response as well as threat security and intelligence. They will share their insights that they have, collaborate on actions, and help to provide a proactive defense against cyberattacks. As we move forward in the future, it's crucial for organizations to embrace the potential of autonomous AI, while taking note of the moral implications and social consequences of autonomous AI systems. Through fostering a culture that promotes accountable AI advancement, transparency and accountability, we can harness the power of agentic AI in order to construct a safe and robust digital future. Conclusion Agentic AI is a breakthrough in the field of cybersecurity. It's a revolutionary approach to recognize, avoid the spread of cyber-attacks, and reduce their impact. The ability of an autonomous agent particularly in the field of automatic vulnerability fix and application security, could aid organizations to improve their security practices, shifting from a reactive strategy to a proactive strategy, making processes more efficient as well as transforming them from generic contextually aware. Agentic AI has many challenges, but the benefits are far enough to be worth ignoring. As we continue pushing the boundaries of AI for cybersecurity It is crucial to adopt a mindset of continuous adapting, learning and sustainable innovation. In this way, we can unlock the full power of agentic AI to safeguard our digital assets, protect our companies, and create better security for everyone.