The Rise of Shadow AI: Risks Every Organization Should Understand Most organizations have heard of shadow IT, but a new challenge is rapidly emerging: Shadow AI. Employees are increasingly using generative AI tools to improve productivity, automate tasks, and solve business problems. Unfortunately, many of these tools operate outside organizational oversight. An AI Utilization Assessment […]
AI Utilization AssessmentWhat Is an AI Utilization Assessment and Why Does Your Organization Need One? Organizations are investing heavily in artificial intelligence, yet many struggle to answer a simple question: How is AI actually being used across the business? Without visibility into AI adoption, leadership teams may overlook security risks, duplicate investments, compliance concerns, and missed opportunities […]
AI Utilization AssessmentAI Application Penetration Testing: Expanding Traditional Security Assessments Traditional penetration testing remains an essential component of cybersecurity programs, but AI-powered applications introduce new risks that require specialized expertise. AI Penetration Testing combines traditional offensive security methodologies with AI-specific attack scenarios. How AI Applications Differ AI applications often include: LLM integrations External data sources Dynamic content […]
AI Security TestingModel Extraction Attacks: Protecting Your AI Intellectual Property AI models often represent significant investments in data, research, development, and business strategy. As AI becomes more valuable, attackers increasingly seek to steal or replicate proprietary models. Model Extraction Testing helps organizations evaluate the risk of unauthorized model replication. What Is Model Extraction? Model extraction occurs when […]
AI Security TestingSecuring AI APIs: The Overlooked Attack Surface Many AI applications rely on APIs to interact with models, databases, cloud services, and third-party platforms. Unfortunately, APIs remain one of the most frequently exploited components within modern architectures. AI API Security Testing helps organizations identify vulnerabilities before attackers can leverage them. Common AI API Risks Authentication Weaknesses […]
AI Security TestingUnderstanding Adversarial Attacks Against AI Systems Adversarial attacks are among the most concerning threats facing modern AI systems. These attacks intentionally manipulate model inputs to produce incorrect, unsafe, or unexpected outputs. As organizations increasingly depend on AI for business operations, understanding adversarial testing has become essential. What Is an Adversarial Attack? Adversarial attacks involve carefully […]
AI Security TestingWhy AI Security Testing Is Essential for Modern Organizations Artificial Intelligence is transforming business operations, but it is also introducing new attack surfaces that traditional security programs were never designed to address. From large language models and AI-powered applications to machine learning pipelines and integrated data systems, organizations are deploying technologies that require specialized security […]
AI Security TestingEvaluating Data Leakage Risks in Large Language Models Data protection remains one of the most important concerns in AI deployments. Organizations frequently connect LLMs to internal knowledge bases, customer records, proprietary documents, and other sensitive information. Without proper safeguards, AI systems may expose data in unintended ways. AI LLM Testing can mitigate these risks. What […]
AI LLM TestingAI Red Teaming: Stress Testing Large Language Models Cybersecurity teams have long used red team exercises to evaluate defenses. Today, organizations are applying similar techniques to AI systems through AI Red Teaming. This approach simulates real-world attacks against large language models to identify weaknesses before adversaries exploit them. What Is AI Red Teaming? AI red […]
AI LLM Testing