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Introduction Artificial intelligence (AI), in the continually evolving field of cyber security has been utilized by businesses to improve their defenses. As threats become more complex, they are increasingly turning to AI. While AI is a component of cybersecurity tools since a long time and has been around for a while, the advent of agentsic AI can signal a new age of active, adaptable, and connected security products. The article focuses on the potential of agentic AI to revolutionize security including the application of AppSec and AI-powered automated vulnerability fixing. Cybersecurity A rise in Agentic AI Agentic AI can be which refers to goal-oriented autonomous robots able to perceive their surroundings, take decisions and perform actions for the purpose of achieving specific targets. Agentic AI is distinct from traditional reactive or rule-based AI as it can change and adapt to its surroundings, as well as operate independently. When it comes to security, autonomy can translate into AI agents that are able to continually monitor networks, identify suspicious behavior, and address attacks in real-time without constant human intervention. The power of AI agentic in cybersecurity is vast. Through the use of machine learning algorithms and huge amounts of information, these smart agents can detect patterns and relationships which human analysts may miss. The intelligent AI systems can cut through the noise of several security-related incidents and prioritize the ones that are crucial and provide insights to help with rapid responses. Agentic AI systems have the ability to learn and improve their capabilities of detecting risks, while also being able to adapt themselves to cybercriminals' ever-changing strategies. Agentic AI (Agentic AI) and Application Security Agentic AI is a powerful instrument that is used in many aspects of cyber security. But the effect its application-level security is notable. The security of apps is paramount in organizations that are dependent increasingly on complex, interconnected software systems. The traditional AppSec methods, like manual code review and regular vulnerability scans, often struggle to keep up with the rapid development cycles and ever-expanding vulnerability of today's applications. Agentic AI could be the answer. Through the integration of intelligent agents into software development lifecycle (SDLC) organizations can transform their AppSec practice from proactive to. AI-powered agents are able to constantly monitor the code repository and analyze each commit in order to identify possible security vulnerabilities. They employ sophisticated methods including static code analysis test-driven testing and machine learning, to spot a wide range of issues, from common coding mistakes as well as subtle vulnerability to injection. The agentic AI is unique in AppSec since it is able to adapt and learn about the context for each and every application. Agentic AI is able to develop an extensive understanding of application design, data flow and attack paths by building the complete CPG (code property graph) that is a complex representation that captures the relationships between code elements. The AI can identify vulnerability based upon their severity in actual life, as well as what they might be able to do in lieu of basing its decision upon a universal severity rating. Artificial Intelligence and Intelligent Fixing Automatedly fixing vulnerabilities is perhaps the most fascinating application of AI agent within AppSec. Human programmers have been traditionally required to manually review code in order to find vulnerabilities, comprehend the issue, and implement the solution. This can take a lengthy period of time, and be prone to errors. It can also delay the deployment of critical security patches. Through agentic AI, the game has changed. Through the use of the in-depth understanding of the codebase provided by the CPG, AI agents can not only identify vulnerabilities and create context-aware not-breaking solutions automatically. Intelligent agents are able to analyze the code surrounding the vulnerability and understand the purpose of the vulnerability, and craft a fix that corrects the security vulnerability without adding new bugs or damaging existing functionality. The benefits of AI-powered auto fixing are huge. It is estimated that the time between finding a flaw before addressing the issue will be reduced significantly, closing an opportunity for criminals. It can also relieve the development group of having to devote countless hours fixing security problems. The team are able to concentrate on creating new features. In addition, by automatizing the fixing process, organizations are able to guarantee a consistent and reliable method of vulnerabilities remediation, which reduces risks of human errors or errors. The Challenges and the Considerations Though the scope of agentsic AI in cybersecurity as well as AppSec is vast however, it is vital to be aware of the risks as well as the considerations associated with its adoption. Accountability and trust is a crucial issue. Companies must establish clear guidelines for ensuring that AI operates within acceptable limits as AI agents develop autonomy and are able to take the decisions for themselves. This includes the implementation of robust verification and testing procedures that confirm the accuracy and security of AI-generated fix. The other issue is the threat of an attacks that are adversarial to AI. Hackers could attempt to modify the data, or make use of AI weakness in models since agents of AI systems are more common within cyber security. This underscores the necessity of security-conscious AI techniques for development, such as techniques like adversarial training and model hardening. Additionally, the effectiveness of agentic AI used in AppSec is heavily dependent on the completeness and accuracy of the code property graph. this link of creating and maintaining an accurate CPG is a major budget for static analysis tools and frameworks for dynamic testing, and data integration pipelines. Organizations must also ensure that they are ensuring that their CPGs correspond to the modifications that occur in codebases and changing threat landscapes. The future of Agentic AI in Cybersecurity However, despite the hurdles that lie ahead, the future of AI for cybersecurity is incredibly positive. We can expect even better and advanced autonomous agents to detect cybersecurity threats, respond to them, and diminish their effects with unprecedented agility and speed as AI technology develops. Agentic AI inside AppSec can alter the method by which software is created and secured and gives organizations the chance to develop more durable and secure apps. Additionally, the integration of artificial intelligence into the broader cybersecurity ecosystem provides exciting possibilities for collaboration and coordination between the various tools and procedures used in security. Imagine a scenario where autonomous agents are able to work in tandem through network monitoring, event reaction, threat intelligence and vulnerability management. Sharing insights as well as coordinating their actions to create a comprehensive, proactive protection against cyber attacks. In the future we must encourage companies to recognize the benefits of artificial intelligence while paying attention to the moral implications and social consequences of autonomous system. The power of AI agentics to design security, resilience, and reliable digital future by creating a responsible and ethical culture to support AI development. Conclusion In the fast-changing world in cybersecurity, agentic AI will be a major shift in the method we use to approach the prevention, detection, and elimination of cyber risks. With the help of autonomous AI, particularly for app security, and automated fix for vulnerabilities, companies can improve their security by shifting by shifting from reactive to proactive, from manual to automated, and also from being generic to context aware. There are many challenges ahead, but the advantages of agentic AI can't be ignored. leave out. In the midst of pushing AI's limits when it comes to cybersecurity, it's vital to be aware of constant learning, adaption, and responsible innovations. We can then unlock the power of artificial intelligence for protecting digital assets and organizations.