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AI tools are only as effective as the data they learn from. For the first time, the industry has tools to make this data accessible and meaningful. Let's look at how the industry sees AI SOC agents and how to maximize the use of their data sources.

Stream.Security just launched a new AI Triage feature to assist analysts in addressing the growing volume of alerts in the cloud and SaaS. The AI Triage agent brings human-like intelligence and decision making to SOC analysts. With Stream’s real-time CloudTwin model, the triage digests updated risk-based data that factors in asset criticality, exposure, and blast radius to prioritize alerts that truly matter.

Stream delivers cloud-native detection engines, from rules and anomalies to canaries, as part of our Cloud Detection & Response (CDR) platform.Traditional canaries are siloed, making them hard to scale, hard to manage, and often ignored. Stream takes canaries further by embedding them into the CloudTwin™ fabric.

When we talk about cloud hardening, encryption, patching, and zero-day detection usually get all the spotlight. But in reality, the single most important factor in reducing breach impact is blast radius reduction. That comes down to two things: identity segmentation and network segmentation.

Let’s dive in to our first attack scenario together: CDRGoat Scenario 2. This scenario demonstrates how a simple but popular web application vulnerability, SSRF, can escalate into complete AWS account compromise. We'll walk through a realistic attack chain that leverages common cloud misconfigurations rather than obvious security flaws.

Get started with Stream's CDRGoat! This post will walk through how to set up your environment, run your first scenario and start gaining value from the detections it generates.

Stream's CDRGoat is an open-source project that lets SecOps teams safely validate detections and investigations against realistic cloud attack paths. Each scenario, developed by Stream’s Security Research and Product teams, includes vulnerable infrastructure and walks through a guided live attack to show exactly how adversaries exploit cloud environments in practice.

Stream now integrates with Salesforce for advanced threat detection. The integration provides in-depth detection capabilities that will help you catch Salesforce breaches in real time, including the recent Salesloft Drift compromise.

For large-scale cloud environments, the math is simple. When detections depend on stale data, triage is manual, and investigations are fragmented, even the best teams fall behind. Stream’s platform gives SecOps teams complete cloud visibility in real-time, with built-in automations and AI tooling that make investigations easy.

Stream now integrates Snowflake audit logs directly into our SaaS and cloud detection framework. By including Snowflake activity as part of SaaS-sourced signals, we give SecOps teams complete visibility into how threats unfold across the chain of services connected to the cloud. This unified view closes the gaps that attackers target to ensure Snowflake is protected not just in isolation, but as part of the bigger cloud story.