Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The way we build software has fundamentally changed. AI code assistants are no longer a novelty; they are the new standard, creating a revolutionary leap in developer productivity. Back in May, we launched Snyk Studio with a focus on our partners, creating an open framework to build a vibrant ecosystem for securing AI-driven development. Our goal was to ensure that as the AI landscape evolved, Snyk’s market-leading security intelligence could be embedded into any AI-native tool.

The Model Context Protocol (MCP) is a popular framework for connecting AI agents to data sources, such as APIs and databases. Because this technology is still new and evolving, its security standards are also in the early stages. This means that MCP servers are susceptible to misuse, so teams building and running them internally need visibility into server interactions to keep their environments safe from attacks.

Attackers can more easily introduce malicious data into AI models than previously thought, according to a new study from Antropic. Poisoned AI models can produce malicious outputs, leading to follow-on attacks. For example, attackers can train an AI model to provide links to phishing sites or plant backdoors in AI-generated code.

Traditional SIEMs were built for a simpler time, when infrastructure was static, data was structured, and threats were easier to spot. Designed to collect logs and centralize alerts, they gave organizations a single pane of glass into their environment. Visibility isn’t enough anymore.