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What is agentic AI and how does this differ from the traditional AI used in cybersecurity? Agentic AI refers to autonomous, goal-oriented systems that can perceive their environment, make decisions, and take actions to achieve specific objectives. Agentic AI is a more flexible and adaptive version of traditional AI. In link here , agentic AI enables continuous monitoring, real-time threat detection, and proactive response capabilities. What are some examples of real-world agentic AI in cybersecurity? continuous ai security is used in cybersecurity. Autonomous threat detection and response platforms that continuously monitor networks and endpoints for malicious activity AI-powered vulnerability scanners that identify and prioritize security flaws in applications and infrastructure Intelligent threat intelligence systems gather data from multiple sources and analyze it to provide proactive protection against emerging threats Autonomous incident response tools that can contain and mitigate cyber attacks without human intervention AI-driven solutions for fraud detection that detect and prevent fraudulent activity in real time How can agentic AI help bridge the skills gap in cybersecurity and alleviate the burden on security teams? Agentic AI helps to address the cybersecurity skills gaps by automating repetitive and time-consuming security tasks currently handled manually. By taking on tasks such as continuous monitoring, threat detection, vulnerability scanning, and incident response, agentic AI systems can free up human experts to focus on more strategic and complex security challenges. Additionally, ai security tool requirements and recommendations provided by agentic AI can help less experienced security personnel make more informed decisions and respond more effectively to potential threats. What are the implications of agentic AI on compliance and regulatory requirements for cybersecurity? Agentic AI helps organizations to meet compliance and regulation requirements more effectively. It does this by providing continuous monitoring and real-time threat detection capabilities, as well as automated remediation. Autonomous agents ensure that security controls and vulnerabilities are addressed promptly, security incidents are documented, and reports are made. The use of agentic AI raises new compliance concerns, including ensuring transparency, accountability and fairness in AI decision-making, as well as protecting privacy and security for data used to train and analyze AI. For organizations to successfully integrate agentic artificial intelligence into existing security tools, they should: Assess the current security infrastructure to identify areas that agentic AI could add value. Develop a clear strategy and roadmap for agentic AI adoption, aligned with overall security goals and objectives Make sure that AI agent systems are compatible and can exchange data and insights seamlessly with existing security tools. Provide training and support for security personnel to effectively use and collaborate with agentic AI systems Create governance frameworks to oversee the ethical and responsible use of AI agents in cybersecurity What are some emerging trends and future directions for agentic AI in cybersecurity? https://www.linkedin.com/posts/qwiet_gartner-appsec-qwietai-activity-7203450652671258625-Nrz0 emerging trends and future directions for agentic AI in cybersecurity include: Increased collaboration and coordination between autonomous agents across different security domains and platforms AI models with context-awareness and advanced capabilities that adapt to dynamic and complex security environments Integration of agentic AI with other emerging technologies, such as blockchain, cloud computing, and IoT security Exploration of novel approaches to AI security, such as homomorphic encryption and federated learning, to protect AI systems and data Advancement of explainable AI techniques to improve transparency and trust in autonomous security decision-making How can AI agents help protect organizations from targeted and advanced persistent threats? Agentic AI provides a powerful defense for APTs and targeting attacks by constantly monitoring networks and systems to detect subtle signs of malicious behavior. this article can analyze vast amounts of security data in real-time, identifying patterns and anomalies that might indicate a stealthy and persistent threat. Agentic AI, which adapts to new attack methods and learns from previous attacks, can help organizations detect APTs and respond more quickly, minimising the impact of a breach. The following are some of the benefits that come with using agentic AI to monitor security continuously and detect threats in real time: Monitoring of endpoints, networks, and applications for security threats 24/7 Prioritization and rapid identification of threats according to their impact and severity Reduced false positives and alert fatigue for security teams Improved visibility of complex and distributed IT environments Ability to detect new and evolving threats which could evade conventional security controls Security incidents can be dealt with faster and less damage is caused. How can https://www.anshumanbhartiya.com/posts/the-future-of-appsec improve incident response and remediation processes? Agentic AI has the potential to enhance incident response processes and remediation by: Automatically detecting and triaging security incidents based on their severity and potential impact Contextual insights and recommendations to effectively contain and mitigate incidents Automating and orchestrating incident response workflows on multiple security tools Generating detailed reports and documentation to support compliance and forensic purposes Learning from incidents to continuously improve detection and response capabilities Enabling faster and more consistent incident remediation, reducing the overall impact of security breaches To ensure that security teams can effectively leverage agentic AI systems, organizations should: Give comprehensive training about the capabilities, limitations and proper usage of agentic AI tools Encourage security personnel to collaborate with AI systems, and provide feedback on improvements. Develop clear protocols and guidelines for human-AI interaction, including when to trust AI recommendations and when to escalate issues for human review Invest in upskilling programs that help security professionals develop the necessary technical and analytical skills to interpret and act upon AI-generated insights To ensure an holistic approach to the adoption and use of agentic AI, encourage cross-functional collaboration among security, data science and IT teams. How can organizations balance the benefits of agentic AI with the need for human oversight and decision-making in cybersecurity? To strike the right balance between leveraging agentic AI and maintaining human oversight in cybersecurity, organizations should: Assign roles and responsibilities to humans and AI decision makers, and ensure that all critical security decisions undergo human review and approval. Implement transparent and explainable AI techniques that allow security personnel to understand and trust the reasoning behind AI recommendations Develop robust testing and validation processes to ensure the accuracy, reliability, and safety of AI-generated insights and actions Maintain human-in-the-loop approaches for high-stakes security scenarios, such as incident response and threat hunting Encourage a culture that is responsible in the use of AI, highlighting the importance of human judgement and accountability when it comes to cybersecurity decisions. Regularly monitor and audit AI systems to identify potential biases, errors, or unintended consequences, and make necessary adjustments to ensure optimal performance and alignment with organizational security goals