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The following article is an outline of the subject: Artificial intelligence (AI) as part of the continually evolving field of cyber security has been utilized by corporations to increase their security. As the threats get more complicated, organizations tend to turn to AI. Although AI has been a part of the cybersecurity toolkit since the beginning of time however, the rise of agentic AI will usher in a new age of proactive, adaptive, and contextually-aware security tools. The article explores the possibility for the use of agentic AI to change the way security is conducted, and focuses on use cases of AppSec and AI-powered automated vulnerability fixes. The rise of Agentic AI in Cybersecurity Agentic AI can be applied to autonomous, goal-oriented robots that can see their surroundings, make action that help them achieve their desired goals. Contrary to conventional rule-based, reactive AI, agentic AI technology is able to learn, adapt, and function with a certain degree of detachment. For security, autonomy is translated into AI agents that are able to continually monitor networks, identify abnormalities, and react to dangers in real time, without constant human intervention. Agentic AI is a huge opportunity in the area of cybersecurity. Agents with intelligence are able discern patterns and correlations using machine learning algorithms and huge amounts of information. The intelligent AI systems can cut through the noise generated by several security-related incidents prioritizing the crucial and provide insights that can help in rapid reaction. Agentic AI systems can be taught from each encounter, enhancing their ability to recognize threats, and adapting to ever-changing techniques employed by cybercriminals. Agentic AI (Agentic AI) as well as Application Security Agentic AI is a powerful tool that can be used in many aspects of cybersecurity. However, the impact it can have on the security of applications is notable. Security of applications is an important concern in organizations that are dependent ever more heavily on highly interconnected and complex software systems. AppSec tools like routine vulnerability scanning and manual code review do not always keep up with current application development cycles. Agentic AI could be the answer. Incorporating intelligent agents into the lifecycle of software development (SDLC) organisations can transform their AppSec practices from reactive to proactive. The AI-powered agents will continuously monitor code repositories, analyzing every commit for vulnerabilities as well as security vulnerabilities. They are able to leverage sophisticated techniques like static code analysis testing dynamically, and machine learning to identify numerous issues that range from simple coding errors to subtle injection vulnerabilities. Intelligent AI is unique in AppSec due to its ability to adjust and learn about the context for every app. Agentic AI can develop an in-depth understanding of application structure, data flow and attacks by constructing an extensive CPG (code property graph) which is a detailed representation that reveals the relationship between various code components. This contextual awareness allows the AI to prioritize vulnerabilities based on their real-world vulnerability and impact, instead of relying on general severity rating. Artificial Intelligence and Autonomous Fixing The idea of automating the fix for weaknesses is possibly the most interesting application of AI agent within AppSec. Human developers have traditionally been in charge of manually looking over the code to discover vulnerabilities, comprehend it, and then implement the solution. This can take a long time, error-prone, and often causes delays in the deployment of crucial security patches. It's a new game with agentsic AI. AI agents can find and correct vulnerabilities in a matter of minutes using CPG's extensive knowledge of codebase. These intelligent agents can analyze the code surrounding the vulnerability to understand the function that is intended and then design a fix that addresses the security flaw while not introducing bugs, or breaking existing features. The benefits of AI-powered auto fixing have a profound impact. The amount of time between finding a flaw and fixing the problem can be reduced significantly, closing the door to attackers. This can relieve the development group of having to invest a lot of time solving security issues. They could concentrate on creating fresh features. Automating the process of fixing security vulnerabilities allows organizations to ensure that they're utilizing a reliable and consistent method and reduces the possibility to human errors and oversight. What are the main challenges and the considerations? Although the possibilities of using agentic AI in the field of cybersecurity and AppSec is enormous however, it is vital to understand the risks and concerns that accompany its implementation. The issue of accountability and trust is a crucial one. Organizations must create clear guidelines for ensuring that AI acts within acceptable boundaries in the event that AI agents develop autonomy and become capable of taking independent decisions. It is crucial to put in place robust testing and validating processes to guarantee the security and accuracy of AI produced corrections. A further challenge is the potential for adversarial attacks against the AI system itself. Since agent-based AI technology becomes more common in cybersecurity, attackers may attempt to take advantage of weaknesses in the AI models, or alter the data from which they are trained. This underscores the necessity of secured AI techniques for development, such as strategies like adversarial training as well as modeling hardening. The effectiveness of agentic AI in AppSec depends on the accuracy and quality of the graph for property code. Maintaining and constructing an precise CPG will require a substantial expenditure in static analysis tools and frameworks for dynamic testing, as well as data integration pipelines. Companies also have to make sure that their CPGs reflect the changes that take place in their codebases, as well as evolving threat environment. this video of Agentic AI in Cybersecurity Despite the challenges that lie ahead, the future of AI for cybersecurity appears incredibly hopeful. As AI technologies continue to advance it is possible to get even more sophisticated and capable autonomous agents that can detect, respond to, and reduce cyber attacks with incredible speed and accuracy. With regards to AppSec agents, AI-based agentic security has the potential to change how we design and secure software, enabling organizations to deliver more robust as well as secure apps. Moreover, the integration of AI-based agent systems into the wider cybersecurity ecosystem can open up new possibilities to collaborate and coordinate various security tools and processes. Imagine a scenario where the agents work autonomously on network monitoring and response, as well as threat information and vulnerability monitoring. They would share insights that they have, collaborate on actions, and offer proactive cybersecurity. Moving forward as we move forward, it's essential for businesses to be open to the possibilities of AI agent while cognizant of the social and ethical implications of autonomous systems. If we can foster a culture of accountable AI development, transparency and accountability, we are able to make the most of the potential of agentic AI for a more safe and robust digital future. Conclusion In the fast-changing world in cybersecurity, agentic AI will be a major change in the way we think about the prevention, detection, and mitigation of cyber threats. Through the use of autonomous agents, specifically when it comes to application security and automatic security fixes, businesses can change their security strategy from reactive to proactive from manual to automated, and also from being generic to context aware. There are many challenges ahead, but the benefits that could be gained from agentic AI are too significant to not consider. While we push AI's boundaries for cybersecurity, it's crucial to remain in a state of continuous learning, adaptation and wise innovations. We can then unlock the potential of agentic artificial intelligence in order to safeguard businesses and assets.