Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI is no longer a futuristic concept – It has now become the core of how modern businesses are operating. Starting from chatbots to analytics, generative content to automation, AI is across every sector of business. As AI usage increases, the risks and regulation are also increasing.

The companies winning with AI aren’t just deploying agents faster - they’re operationalizing them responsibly. They realize AI agents are creating a new, dynamic attack surface that traditional tools were never designed to handle. These agents span the entire enterprise ecosystem. Microsoft 365 Copilot, Copilot Studio, and Salesforce Agentforce are SaaS‑managed agents. GitHub Copilot, Cursor, and Claude desktop run directly on user devices as device‑based agents.

Read key insights from GitGuardian SecDays Virtual 2025 on securing the future of autonomous AI agents.

At Snyk, we believe you should never have to choose between speed and security. As the age of AI transforms software development, our goal is to extend our developer-first security approach to this new era, providing the essential tools your teams need to build with confidence. Today at Black Hat, we are delivering on that vision with three tangible innovations that offer a comprehensive solution to secure the entire code lifecycle with AI.

The AI battleground is here. Adversaries are weaponizing AI to launch attacks with unprecedented scale, speed, and effectiveness. In response, defenders are turning to AI as an analyst force-multiplier, using it to offload repetitive tasks, accelerate decision-making, and scale expertise across the SOC.

Today’s enterprising adversaries are weaponizing AI to scale operations, accelerate attacks, and target the autonomous AI agents quickly transforming modern businesses. The CrowdStrike 2025 Threat Hunting Report details this new chapter in the threat landscape. This year’s report, based on frontline intelligence from CrowdStrike’s elite threat hunters and intelligence analysts, examines how threat actors are using AI to do more with less.

Data poisoning occurs when cyber criminals intentionally compromise the integrity of a data set used for training machine learning models. They corrupt the information to manipulate the model’s outcome in the form of incorrect predictions by introducing vulnerabilities that reduce the effectiveness, add security risks, and fundamentally shape its decision making capabilities.