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this video (AI) which is part of the continually evolving field of cyber security is used by businesses to improve their security. Since threats are becoming more sophisticated, companies have a tendency to turn to AI. AI was a staple of cybersecurity for a long time. been part of cybersecurity, is now being re-imagined as agentic AI, which offers proactive, adaptive and contextually aware security. This article examines the possibilities of agentic AI to change the way security is conducted, with a focus on the application to AppSec and AI-powered automated vulnerability fixing. Cybersecurity A rise in Agentic AI Agentic AI is a term used to describe goals-oriented, autonomous systems that can perceive their environment to make decisions and implement actions in order to reach particular goals. As opposed to the traditional rules-based or reactive AI systems, agentic AI systems possess the ability to adapt and learn and work with a degree of detachment. For cybersecurity, this autonomy translates into AI agents that constantly monitor networks, spot irregularities and then respond to security threats immediately, with no any human involvement. Agentic AI offers enormous promise in the area of cybersecurity. These intelligent agents are able to detect patterns and connect them by leveraging machine-learning algorithms, and huge amounts of information. They can sift through the noise of countless security events, prioritizing the most crucial incidents, and providing actionable insights for swift response. Agentic AI systems can be trained to learn and improve their ability to recognize threats, as well as changing their strategies to match cybercriminals' ever-changing strategies. Agentic AI (Agentic AI) as well as Application Security Although agentic AI can be found in a variety of application in various areas of cybersecurity, its influence on the security of applications is notable. The security of apps is paramount for companies that depend ever more heavily on interconnected, complex software technology. Standard AppSec approaches, such as manual code reviews, as well as periodic vulnerability scans, often struggle to keep up with the speedy development processes and the ever-growing threat surface that modern software applications. Agentic AI can be the solution. Through the integration of intelligent agents in the lifecycle of software development (SDLC) organisations can change their AppSec methods from reactive to proactive. AI-powered agents can continually monitor repositories of code and scrutinize each code commit to find weaknesses in security. They employ sophisticated methods including static code analysis dynamic testing, and machine learning to identify the various vulnerabilities that range from simple coding errors to little-known injection flaws. Intelligent AI is unique in AppSec due to its ability to adjust and learn about the context for every app. https://www.youtube.com/watch?v=WoBFcU47soU is capable of developing an intimate understanding of app structure, data flow and attacks by constructing the complete CPG (code property graph) an elaborate representation that shows the interrelations between code elements. This contextual awareness allows the AI to identify vulnerability based upon their real-world impact and exploitability, instead of using generic severity ratings. AI-powered Automated Fixing the Power of AI The notion of automatically repairing security vulnerabilities could be the most intriguing application for AI agent in AppSec. Human developers have traditionally been in charge of manually looking over the code to identify the flaw, analyze it, and then implement fixing it. The process is time-consuming in addition to error-prone and frequently results in delays when deploying crucial security patches. AI hallucinations have changed thanks to agentsic AI. AI agents can identify and fix vulnerabilities automatically using CPG's extensive understanding of the codebase. They can analyse the code around the vulnerability to understand its intended function and then craft a solution that corrects the flaw but creating no new vulnerabilities. AI-powered automation of fixing can have profound implications. It can significantly reduce the period between vulnerability detection and resolution, thereby making it harder for hackers. This can relieve the development team from the necessity to dedicate countless hours fixing security problems. In their place, the team could be able to concentrate on the development of innovative features. Additionally, by automatizing the fixing process, organizations will be able to ensure consistency and reliable method of fixing vulnerabilities, thus reducing the possibility of human mistakes or oversights. What are the issues and considerations? While the potential of agentic AI in cybersecurity and AppSec is enormous however, it is vital to be aware of the risks and concerns that accompany the adoption of this technology. It is important to consider accountability and trust is a key issue. Organizations must create clear guidelines to ensure that AI behaves within acceptable boundaries as AI agents develop autonomy and begin to make the decisions for themselves. This includes implementing robust test and validation methods to confirm the accuracy and security of AI-generated solutions. Another concern is the potential for adversarial attacks against the AI system itself. An attacker could try manipulating data or take advantage of AI model weaknesses since agents of AI platforms are becoming more prevalent in cyber security. It is imperative to adopt secured AI methods such as adversarial and hardening models. The accuracy and quality of the diagram of code properties can be a significant factor in the success of AppSec's agentic AI. To build and keep an accurate CPG it is necessary to invest in instruments like static analysis, testing frameworks, and pipelines for integration. Organizations must also ensure that their CPGs reflect the changes that occur in codebases and the changing threat environments. The future of Agentic AI in Cybersecurity The future of AI-based agentic intelligence for cybersecurity is very optimistic, despite its many problems. As AI technologies continue to advance and become more advanced, we could get even more sophisticated and powerful autonomous systems that are able to detect, respond to, and mitigate cyber threats with unprecedented speed and precision. In the realm of AppSec Agentic AI holds an opportunity to completely change how we design and secure software, enabling businesses to build more durable, resilient, and secure applications. The introduction of AI agentics into the cybersecurity ecosystem opens up exciting possibilities to coordinate and collaborate between cybersecurity processes and software. Imagine a future in which autonomous agents work seamlessly through network monitoring, event response, threat intelligence and vulnerability management. Sharing insights and coordinating actions to provide a comprehensive, proactive protection against cyber threats. In the future, it is crucial for companies to recognize the benefits of artificial intelligence while paying attention to the ethical and societal implications of autonomous technology. We can use the power of AI agentics to create security, resilience as well as reliable digital future through fostering a culture of responsibleness to support AI development. The conclusion of the article will be: Agentic AI is an exciting advancement in the world of cybersecurity. It's an entirely new approach to recognize, avoid attacks from cyberspace, as well as mitigate them. The ability of an autonomous agent specifically in the areas of automated vulnerability fixing and application security, can aid organizations to improve their security posture, moving from being reactive to an proactive security approach by automating processes and going from generic to context-aware. Agentic AI presents many issues, but the benefits are enough to be worth ignoring. As we continue to push the limits of AI in the field of cybersecurity It is crucial to approach this technology with an eye towards continuous learning, adaptation, and responsible innovation. If we do this we will be able to unlock the power of artificial intelligence to guard our digital assets, protect our organizations, and build the most secure possible future for everyone.