JupiterOne targets AI sprawl with new attack surface and vulnerability tools

Artificial intelligence risk management platform provider JupiterOne Inc. today announced the launch of two new offerings aimed at helping security teams get a handle on risk created by the sprawl of AI systems across enterprise environments.

The company pitches the two products, AI Attack Surface Management and Unified Vulnerability Management, as a way to show security teams how assets, vulnerabilities and AI agents tie together into business risk.

JupiterOne argues that AI tools, software-as-a-service applications and cloud resources are being deployed faster than security teams can track them, while AI agents now touch nearly every system and vulnerabilities pile up faster than teams can triage. AI ASM is designed to address that visibility gap.

The offering provides a continually updated, relationship-aware view of enterprise environments, powered by automated discovery through hundreds of integrations. AI ASM maps how AI agents, systems, cloud resources and identities interact in a single place. Security teams can query the underlying data in plain English or through JupiterOne’s native query language to surface what exists, how assets are connected, how they could be exploited and what the potential business impact would be.

“AI has changed the attack surface and new models are increasing the number of potential weaknesses across the industry every day,” said Chief Executive Paul Forte. “Most teams today face tooling fragmentation and work without a clear understanding of how their systems interact. This launch gives defenders a streamlined approach to assessing risk without stitching together separate tools, programs, or teams.”

The second new release, UVM, takes aim at vulnerability prioritization. JupiterOne says that traditional scanners report what is potentially vulnerable and severity scoring systems reflect only theoretical risk, leaving teams without a clear sense of what actually matters. UVM evaluates vulnerabilities in the context of each customer deployment, analyzing the flaw alongside the full attack chain to show what is vulnerable, what it is linked to and how an attacker could move through those paths to reach business-critical assets.

The product also deduplicates findings across tools and identifies asset ownership, which JupiterOne says shortens remediation cycles by routing fixes to the people responsible for them.

Both offerings are built on the company’s graph-native data platform, which underpins its broader AI risk management pitch. JupiterOne markets itself to security teams in highly regulated industries and positions the graph model as a way to query how risk flows across assets, identities and controls rather than relying on static lists.

“Security teams are overwhelmed by the volume of vulnerabilities and lack of context,” said Chief Product Officer Kevin Tonkin. “By connecting vulnerabilities to the assets and attack paths around them and showing who owns what needs to be fixed, JupiterOne helps teams remediate with far greater efficiency.”

JupiterOne has raised $119 million over four rounds. Investors in the company include Bain Capital Ventures, Sapphire Ventures, LifeOmic Security, Cisco Investments, Splunk Ventures, Rain Capital Fund LP, Tribe Capital Management, Heavybit Industries Inc. and Sands Capital Ventures.

Image: JupiterOne