Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

A recent grey-box Salesforce assessment began with a low-privileged standard user account. From that starting point, AigentX mapped native Salesforce APIs and custom objects, identified cloud credentials exposed through misconfigured Field-Level Security, and demonstrated a path beyond Salesforce into the organization’s connected cloud infrastructure.

AI adoption is moving faster than most of us anticipated and, more importantly, faster than most organizations can govern it. Organizations are implementing the use of AI-enabled applications, browser extensions, coding assistants, and automated agents to enable employees to work faster. In many cases, these tools are adopted without security review, procurement approval, or a clear understanding of where organizational data is being sent.

If you’re evaluating API discovery tools right now, you’ve probably already seen a handful of demos that look nearly identical: a clean dashboard, an inventory count, maybe a risk score. What’s harder to see in a 30-minute demo is whether that inventory reflects what’s actually running in production, or just what the vendor’s connectors happened to catch on setup day.

The shift to cloud-native infra has broken the traditional perimeter security model. Modern cloud environments are dynamic, heavily distributed, and identity-driven, creating security challenges that conventional security tools were never built to address. Traditional SIEM and vulnerability management tools lack native capabilities to detect issues in IAM policies, S3 bucket ACLs, or the blast radius of a misconfigured Kubernetes node pool.