Prowler unveils graph-based tool to clarify cloud attack paths

Prowler has introduced a new feature, Attack Path Visualization, aimed at helping organisations identify and understand real-world attack routes within their cloud environments. The addition is designed to address a major security challenge: making sense of how attackers might move laterally across complex cloud setups.

Security leaders have increasingly expressed concern about public cloud environments, with many citing the lack of visibility into how attacks can escalate once inside. Standard security scanners often generate thousands of isolated alerts, leaving teams struggling to prioritise which issues pose genuine risks. Attack Path Visualization seeks to address this by mapping interconnected relationships between cloud resources, showing security teams the wider context of potential vulnerabilities.

The platform creates a knowledge graph that links cloud resources and the findings associated with them. By doing so, it reveals how misconfigurations, permissions, and exposed data could combine to form a chain that attackers might exploit. This provides security teams with an overview of how attackers could potentially escalate privileges, move laterally, and target sensitive assets.

Prowler’s knowledge graph approach stands out by directly linking security findings with the relevant resources in a single connected structure. Analysts can trace how a single misconfiguration may be leveraged in sequence with others, generating multi-step attack paths that would not be apparent from fragmented alerts.

This relationship-aware method aids teams in identifying the highest-impact points in their cloud set-up where intervention would be most effective. Rather than addressing scattered, isolated risks, security professionals can focus on breaking attack chains at their most critical links.

The new knowledge graph feature also runs as the core data source for Lighthouse AI, Prowler’s automated security assistant. Lighthouse AI reasons over the graph to identify attack paths, prioritise risks based on potential impact, recommend remediation steps that are aware of the user’s cloud environment, and automate fixes through Prowler’s MCP-powered workflows within developer tools.

Prowler claims that by integrating this level of context with AI-powered decision-making, the time from attack detection to remediation is reduced significantly. The platform aims to provide clarity for security teams, turning cloud complexity into a concise map that details the ‘full chain’ of potential compromise.

The move comes at a time when research suggests that a majority of security leaders view cloud environments as their most challenging risk area. The challenge of correlating individual alerts, understanding real-world attack paths, and prioritising remediation actions is a persistent issue for teams operating in cloud-native and multi-cloud contexts.

Prowler’s approach combines open-source tooling with a focus on relationship-aware analytics and automated response, targeting what many in the industry recognise as a critical gap in cloud security operations.

“Our mission has always been to bring clarity and autonomy to cloud security. Attack Path Visualization gives teams the complete picture of how risks connect, and Lighthouse AI turns that understanding into instant, actionable decisions. It's another step toward a future where security isn't just faster, it's fundamentally more intelligent,” said Toni de la Fuente, Founder & CEO, Prowler.