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https://www.linkedin.com/posts/qwiet_qwiet-ais-foundational-technology-receives-activity-7226955109581156352-h0jp is a brief description of the topic: Artificial intelligence (AI) which is part of the continually evolving field of cybersecurity it is now being utilized by companies to enhance their defenses. As security threats grow more complex, they tend to turn towards AI. AI, which has long been used in cybersecurity is now being transformed into agentsic AI that provides flexible, responsive and contextually aware security. This article focuses on the transformational potential of AI and focuses on the applications it can have in application security (AppSec) as well as the revolutionary concept of AI-powered automatic fix for vulnerabilities. Cybersecurity is the rise of Agentic AI Agentic AI is the term applied to autonomous, goal-oriented robots that can see their surroundings, make decisions and perform actions that help them achieve their targets. As opposed to the traditional rules-based or reacting AI, agentic systems possess the ability to evolve, learn, and operate with a degree of independence. For ai security problems , that autonomy transforms into AI agents that can constantly monitor networks, spot anomalies, and respond to threats in real-time, without constant human intervention. The application of AI agents in cybersecurity is enormous. By leveraging machine learning algorithms and huge amounts of information, these smart agents can detect patterns and connections that human analysts might miss. They can sift through the chaos of many security events, prioritizing the most crucial incidents, and provide actionable information for swift response. Furthermore, agentsic AI systems can gain knowledge from every incident, improving their detection of threats as well as adapting to changing strategies of cybercriminals. Agentic AI and Application Security Agentic AI is a broad field of application across a variety of aspects of cybersecurity, its influence on application security is particularly significant. In a world where organizations increasingly depend on highly interconnected and complex systems of software, the security of their applications is the top concern. The traditional AppSec techniques, such as manual code review and regular vulnerability checks, are often unable to keep up with the rapidly-growing development cycle and threat surface that modern software applications. Agentic AI can be the solution. Integrating intelligent agents in the Software Development Lifecycle (SDLC), organisations can transform their AppSec practices from reactive to pro-active. These AI-powered systems can constantly examine code repositories and analyze every code change for vulnerability or security weaknesses. They are able to leverage sophisticated techniques such as static analysis of code, testing dynamically, as well as machine learning to find numerous issues such as common code 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 application. By building a comprehensive Code Property Graph (CPG) – a rich diagram of the codebase which captures relationships between various code elements – agentic AI is able to gain a thorough understanding of the application's structure in terms of data flows, its structure, and possible attacks. This awareness of the context allows AI to prioritize vulnerabilities based on their real-world potential impact and vulnerability, instead of basing its decisions on generic severity scores. AI-powered Automated Fixing the Power of AI The notion of automatically repairing weaknesses is possibly the most intriguing application for AI agent within AppSec. Human programmers have been traditionally accountable for reviewing manually the code to identify the vulnerability, understand the problem, and finally implement fixing it. This process can be time-consuming in addition to error-prone and frequently causes delays in the deployment of crucial security patches. With agentic AI, the game is changed. AI agents can discover and address vulnerabilities through the use of CPG's vast knowledge of codebase. The intelligent agents will analyze the code that is causing the issue, understand the intended functionality as well as design a fix that corrects the security vulnerability without creating new bugs or breaking existing features. AI-powered, automated fixation has huge impact. It will significantly cut down the gap between vulnerability identification and repair, closing the window of opportunity to attack. It will ease the burden on the development team as they are able to focus on building new features rather then wasting time working on security problems. Automating the process of fixing security vulnerabilities helps organizations make sure they're utilizing a reliable and consistent process that reduces the risk for human error and oversight. What are the challenges as well as the importance of considerations? While the potential of agentic AI for cybersecurity and AppSec is vast It is crucial to recognize the issues and considerations that come with its adoption. One key concern is the question of confidence and accountability. When AI agents become more self-sufficient and capable of taking decisions and making actions in their own way, organisations should establish clear rules and oversight mechanisms to ensure that the AI operates within the bounds of behavior that is acceptable. It is crucial to put in place reliable testing and validation methods in order to ensure the quality and security of AI created corrections. Another concern is the possibility of attacks that are adversarial to AI. As agentic AI technology becomes more common in the world of cybersecurity, adversaries could be looking to exploit vulnerabilities within the AI models or to alter the data on which they are trained. It is important to use safe AI methods such as adversarial-learning and model hardening. Additionally, the effectiveness of agentic AI within AppSec relies heavily on the quality and completeness of the code property graph. To construct and keep agentic ai devsecops will have to purchase techniques like static analysis, testing frameworks and pipelines for integration. The organizations must also make sure that they ensure that their CPGs constantly updated so that they reflect the changes to the security codebase as well as evolving threat landscapes. Cybersecurity Future of AI-agents The potential of artificial intelligence in cybersecurity appears hopeful, despite all the challenges. Expect even more capable and sophisticated autonomous AI to identify cyber security threats, react to them, and minimize the impact of these threats with unparalleled speed and precision as AI technology continues to progress. For AppSec, agentic AI has an opportunity to completely change the way we build and secure software, enabling enterprises to develop more powerful, resilient, and secure software. The introduction of AI agentics to the cybersecurity industry opens up exciting possibilities for collaboration and coordination between security techniques and systems. Imagine a scenario where the agents are autonomous and work across network monitoring and incident responses as well as threats analysis and management of vulnerabilities. They'd share knowledge that they have, collaborate on actions, and give proactive cyber security. It is essential that companies embrace agentic AI as we develop, and be mindful of its ethical and social consequences. The power of AI agents to build a secure, resilient digital world by fostering a responsible culture in AI development. Conclusion With the rapid evolution of cybersecurity, agentic AI is a fundamental shift in how we approach the identification, prevention and elimination of cyber-related threats. Agentic AI's capabilities especially in the realm of automatic vulnerability repair and application security, can aid organizations to improve their security posture, moving from a reactive approach to a proactive security approach by automating processes as well as transforming them from generic contextually aware. Agentic AI has many challenges, but the benefits are far more than we can ignore. As we continue pushing the boundaries of AI in cybersecurity the need to adopt an eye towards continuous development, adaption, and responsible innovation. It is then possible to unleash the full potential of AI agentic intelligence to secure businesses and assets.