AI Applications in Security Solutions

Those of us in the cybersecurity industry understand AI has been behind much of the tooling used to protect systems and data for years (think adaptive firewalls). That said, some new AI security innovations are worth taking a closer look at when implementing. Take AI IAM (AI-driven Identity Authentication Management). While it can be a critical pillar of Zero Trust, deployment is rarely straightforward. Consider the following: - User Push back and Skepticism Behavior-based authentication and continuous verification can make workers feel distrusted, unnecessarily surveilled and ultimately resistant to adaptation. This is a human response that requires a human-based solution. Use behavior-based authentication as a precision tool, not a blanket solution. Employ step-up authentication only for high-risk access and roll out the new tool with a thoughtfully crafted change management approach. - Legacy Systems Integration Many legacy apps lack the ability to integrate well with many AI-driven tools. Use identity orchestration platforms to bridge modern and legacy IAM, figure out a prioritization metric for apps for refactoring or deprecation, and find places where a proxy-based solution makes more sense. - False Positives & Access Disruptions AI is a powerful tool…that still makes mistakes. Its risk scoring can generate excessive authentication challenges or access denials. The last thing you need is a company executive locked out of their email because they bought a new smartphone without telling the IT department. This is where the "learning" part of ML models come in. Instead of static rules, adjust risk guardrails based on sessions and incorporate real-world activities in model training. - Insider Threats & Privileged Access Risks As of this writing, traditional IAM has a spotty track record of detecting credential misuse. Often, a flood of false positives is the result of poorly tuned systems. Use your safety nets: Enforce continuous verification for sensitive roles and implement just-in-time access. - Compliance & AI Governance It can be difficult to clearly understand AI decisions and that makes audits and regulatory reporting difficult. Depending on the enterprise, simply having a "Reasoning" button won't cut it. This is where AI can solve its own problem by "chaining" AI platforms. Consider whether implementing explainable AI (XAI) for risk-based or highly sensitive access is a needed element. And, IAM policy enforcement can still be automated safely, as can assurance testing against established and predictable compliance baselines. But CISOs will need to take into account human behavior and be mindful of very specific organizational needs and use cases to implement it effectively.

Cybersecurity scaling is here. Vulnerabilities can now be scaled with Agentic AI See Video Check out the NIM pre trained models + Nemo framework video. Nvidia has introduced several innovative solutions to scale cybersecurity using Agentic AI, addressing critical concerns like trust, safety, security, and compliance in AI applications. These solutions are designed to help enterprises improve the safety, precision, and scalability of their generative AI applications, particularly in the realm of cybersecurity. NIM Agent Blueprint for Cybersecurity Nvidia has launched a NIM Agent Blueprint for cybersecurity, which combines several of Nvidia’s advanced technologies: 1. Morpheus cybersecurity AI framework 2. Nvidia cuVS 3. Rapids data analytics This blueprint is designed to accelerate the detection of vulnerabilities (CVEs) at scale. It enables enterprises to use generative AI to digest information and explain vulnerabilities using natural language, allowing companies to create agents for cybersecurity workflows. NeMo Guardrails Microservices Nvidia has introduced three new NIM (Nvidia Inference Microservices) for NeMo Guardrails, which are crucial for maintaining controlled behavior in AI agents: 1. Content safety NIM microservice: This safeguards AI against generating biased or harmful outputs, ensuring responses align with ethical standards. 2. Topic control NIM microservice: It keeps conversations focused on approved topics, avoiding digression or inappropriate content. 3. Jailbreak detection NIM microservice: This adds protection against jailbreak attempts, helping maintain AI integrity in adversarial scenarios. These microservices leverage small language models (SLMs) with lower latency than LLMs, making them ideal for scaling AI applications in resource-constrained or distributed environments. Key Benefits for Cybersecurity 1. Improved Safety: The content safety microservice, trained on the Aegis Content Safety Dataset, helps prevent AI from generating harmful or biased outputs. 2. Enhanced Focus: The topic control microservice keeps AI agents on track, preventing them from discussing unauthorized topics or competitor products. 3. Increased Security: The jailbreak detection microservice, built on Nvidia Garak, protects against attempts to bypass an AI agent’s safeguards. 4. Scalability: These solutions are designed to operate efficiently in various environments, including healthcare, automotive, and manufacturing sectors. 5. Customization: NeMo Guardrails allow for customization and extension of rails to meet specific industry + geographical regulatory requirements. By implementing these Nvidia solutions, enterprises can create more secure, trustworthy AI agents that provide safe, appropriate responses within context-specific guidelines. This approach not only boosts customer satisfaction + trust but also addresses the critical cybersecurity challenges faced in the era of AI-driven applications. #CEO #CISO #Cybersecurity

Revolutionizing ethical hacking—AI is changing the way we protect against cyber threats. Gone are the days of time-consuming manual assessments. With AI-driven tools, ethical hackers can identify and patch vulnerabilities faster and more effectively than ever before. Here’s how AI is leading the charge in transforming ethical hacking: 1️⃣ Automated Vulnerability Scanning ↳ Tools like Senteon, CheckRed and CYRISMA automate the scanning process, quickly identifying security gaps such as SQL injections. This allows for more frequent checks and quicker fixes. 2️⃣ Enhanced Threat Detection ↳ AI analyzes vast data sets to detect abnormal patterns, adapting to new attack methods and enabling preemptive threat responses. 3️⃣ Natural Language Processing for Command Execution ↳ Tools like Nebula allow ethical hackers to input commands in simple language, improving speed and accessibility. 4️⃣ Intelligent Risk Prioritization ↳ AI ranks vulnerabilities by severity, helping hackers focus on the most critical threats first and allocate resources effectively. 5️⃣ Continuous Learning and Improvement ↳ AI systems evolve by learning from past data and incidents, staying ahead of emerging threats and improving security responses over time. AI is a game-changer in cybersecurity, making the fight against digital threats more efficient and proactive. Where do you see AI taking cybersecurity next? Let’s chat in the comments!

𝗗𝗮𝘆 𝟭𝟮: 𝗟𝗲𝘃𝗲𝗿𝗮𝗴𝗲 𝗔𝗜/𝗚𝗲𝗻𝗔𝗜 𝘁𝗼 𝗳𝗶𝗴𝗵𝘁 𝗮𝗱𝘃𝗲𝗿𝘀𝗮𝗿𝗶𝗲𝘀 One of the most pressing challenges in cybersecurity today is the global talent shortage, with 𝗮𝗽𝗽𝗿𝗼𝘅𝗶𝗺𝗮𝘁𝗲𝗹𝘆 𝟯.𝟱 𝗺𝗶𝗹𝗹𝗶𝗼𝗻 𝘂𝗻𝗳𝗶𝗹𝗹𝗲𝗱 𝗽𝗼𝘀𝗶𝘁𝗶𝗼𝗻𝘀 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝗲𝗱 𝗯𝘆 𝟮𝟬𝟮𝟱. This gap poses substantial risks, as unfilled roles lead to increased vulnerabilities, cyberattacks, data breaches, and operational disruptions. While there are learning paths like 𝗩𝗶𝘀𝗮’𝘀 𝗣𝗮𝘆𝗺𝗲𝗻𝘁𝘀 𝗖𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗰𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗽𝗿𝗼𝗴𝗿𝗮𝗺 to help aspiring cyber professionals upskill and build careers, Generative AI (GenAI) and Agentic AI offers a scalable solution by augmenting existing teams. Together, they can handle repetitive tasks, automate workflows, enhance incident triaging, and automate code fixes and vulnerability management, enabling smaller teams to scale and maintain robust security postures. Additionally, they enhance cybersecurity efforts by improving defenses while keeping humans in the loop to make critical, informed decisions. Here are few concept about GenAI in Cybersecurity that I’m particularly excited about: 1. Reducing Toil and Improving Team Efficiency GenAI can significantly reduce repetitive tasks, enabling teams to focus on strategic priorities: • GRC : Automates risk assessments, compliance checks, and audit-ready reporting. • DevSecOps: Integrates AI-driven threat modeling and vulnerability scanning into CI/CD pipelines. • IAM : Streamlines user access reviews, provisioning, and anomaly detection. 2. Extreme Shift Left GenAI can rapidly enhance “Secure-by-Design” into development processes by: • Detecting vulnerabilities during coding and providing actionable fixes. • Automating security testing, including fuzzing and penetration testing. 3. Proactive Threat Hunting and Detection Engineering GenAI can enhance threat hunting by: • Analyzing logs and sensor data to detect anomalies. • Correlating data to identify potential threats. • Predicting and detecting attack vectors to arm the sensors proactively. 4. Enabling SOC Automation Security Operations Centers (SOCs) can benefit from GenAI by: • Automating false positive filtering and alert triaging. • Speeds up analysis and resolution with AI-powered insights. • Allowing analysts to concentrate on high-value incidents and strategic decision-making. 𝟱. Enhancing Training and Awareness • Delivering tailored training simulations for developers and business users. • Generating phishing campaigns to educate employees on recognizing threats. In 2025, I am excited about the transformative opportunities that lie ahead. Our focus remains steadfast on innovation and resilience, particularly in leveraging the power of Gen/Agentic AI to enhance user experience, advance our defenses and further strengthen the posture of the payment ecosystem.   #VISA #Cybersecurity #PaymentSecurity #12DaysofCybersecurity #AgenticAI

🙋♀️ I am back with yet another post on AI in Cyber! This past week, I attended a session hosted by Women in CyberSecurity (WiCyS) and SentinelOne. The star of the show was Purple AI, an AI security analyst that works 24/7 to keep your organization safe. What sets it apart is its ability to use natural language processing to understand and respond to complex security queries. Imagine asking, "Am I being targeted by FIN7?" and getting an instant, comprehensive analysis drawn from all your organizational data sources. Here are some key features that caught my attention: 🏇 Faster threat hunting and investigations 🏇 Simplification of threat hunting processes 🏇 Reduction in complexity for security operations I believe AI based security analysts like these have the ability to accelerate SecOps with their speedy analyses, auto-summaries, and suggested queries.   Well, does this mean we don’t need human analysts anymore? Absolutely not. With the power of such tools, humans can focus on what they do best, which is applying critical thinking to complex security challenges. By combining the speed and scalability of AI with the nuanced understanding of human experts, we're entering a new era of cybersecurity defense and I'm super excited to be a part of this transformation. What are your thoughts on AI-powered security tools like Purple AI? #AIinCybersecurity #PurpleAI #ThreatHunting #WomenInTech #SentinelOne #aiincyber #WomenInTech #WomenInCybersecurity #WiCyS #securityoperations #secops #AISecuritytools #CyberIntelligence Adriana Corona Mani Keerthi N Betty Cheng

Reactive security isn’t enough anymore. In today's hyper-connected world, cyberattacks strike with speed—and often, stealth. That’s why AI-powered predictive analytics is becoming the game-changer in modern cybersecurity. Rather than waiting for threats to surface, organizations can now anticipate and neutralize them before they cause damage. 🔍 What does this look like in action? • AI sifting through terabytes of log data in real-time • Flagging anomalies like late-night data exfiltration • Scoring threats based on real-world patterns • Automating defense responses in milliseconds From financial institutions to healthcare systems, predictive models are helping security teams act faster, smarter, and more proactively. 💡 If you're not building predictive capabilities into your security strategy, you’re already one step behind. 🧠 Read the full post to understand how AI is transforming cybersecurity from reactive to revolutionary #Cybersecurity #AI #PredictiveAnalytics #MachineLearning #ThreatDetection #Infosec #DigitalDefense #CISO #CTO #CyberThreats #LesOttolenghi #TechLeadership