Cloud security teams, especially MSSPs, rarely struggle with visibility. The problem is volume without context. Traditional cloud scanners surface hundreds or thousands of findings per customer, but offer little insight into how those issues relate to one another or which ones truly matter.
Prowler’s new Attack Path Visualization is designed to shift the conversation from raw alert counts to connected risk.
At the center of the release is a unified knowledge graph that maps cloud resources, identities, permissions, and data access together with their relationships. Findings are not handled as isolated alerts. They are tied directly into the graph, allowing analysts to see how multiple small weaknesses can combine into a realistic attack route.
Toni de la Fuente, CEO and Founder of Prowler, points to this gap as the core issue MSSPs deal with every day. He told MSSP Alert, “The core problem MSSPs face is drowning in thousands of disconnected alerts from multiple customer environments. Every scanner spits out findings, but there's no connection between them. Their analysts end up chasing individual misconfigurations that might not even matter in context.”
Seeing How Attacks Actually Happen
Attack Path Visualization changes how risk surfaces by making those connections visible. Instead of reviewing long lists of findings by severity, teams can see how exposure, identity, and permissions interact across an environment.
As de la Fuente explains, “Instead of getting ‘Customer A has 847 alerts,’ MSSP teams see the actual chains of risk: how a misconfigured IAM role, an exposed instance, and an overly permissive storage bucket combine to create a real path to sensitive data.” This allows analysts to filter out noise quickly and focus on the paths that end somewhere meaningful.
If a vulnerability has no viable route to sensitive systems, it drops in priority. If a chain exists that leads from a public-facing entry point to critical data or administrative access, it becomes an immediate focus. The result is less time chasing individual issues and more time breaking attack paths that actually matter.
Prioritization Based on Attackability, Not Guesswork
Severity scores have long been a point of friction between MSSPs and customers. Critical findings do not always reflect real-world risk in a specific environment. Prowler addresses this by defining risk through attackability rather than static scoring.
“This is where Prowler takes a really practical stance,” says de la Fuente. “Lighthouse AI can prioritize findings based on real attackability rather than static severity.” A finding may score high on paper, but in practice, it may not be exposed, may lack any lateral movement path, or may be walled off from sensitive systems.
Prowler evaluates whether an attacker can realistically reach an asset and whether that access leads to anything valuable. Attackable paths are defined through three factors: external exposure, lateral movement potential, and access to high-value targets. Only when those elements connect does a risk rise to the top.
“For MSSPs, this is great for consistent prioritization across customers,” de la Fuente notes. “Instead of each customer arguing why their ‘critical’ findings are different, they can be shown the attack path, the entry point, and where it leads. That makes it much easier to explain why one issue takes priority over another.”
Making Cloud Risk Easier to Explain
Beyond triage and response, attack path visualization plays a major role in how MSSPs communicate risk to customers. Explaining cloud security through spreadsheets and severity charts often fails to resonate with business stakeholders.
“Cloud security is complex, and most customers’ eyes glaze over when they’re handed a spreadsheet of hundreds of findings,” de la Fuente says. “Attack path visualization turns abstract risk into a visual story.” Instead of technical descriptions, teams can walk clients through a clear path showing how an attacker could move from a public-facing service to sensitive systems.
This approach helps customers understand both the risk and the reasoning behind remediation recommendations. “Non-technical stakeholders can actually see the risk chain without needing to understand cloud architecture,” de la Fuente explains. That clarity supports faster agreement on remediation priorities, stronger quarterly reviews, and more productive security conversations overall.
Attack Path Visualization is available in preview within Prowler Cloud and integrates directly with Lighthouse AI and MCP-powered workflows. Together, they allow MSSPs to not only identify meaningful attack paths but also automate remediation at scale. With its open-source foundation and flexible architecture, Prowler aims to help service providers reduce alert noise, prioritize consistently, and explain cloud risk in terms customers can actually understand.
