Zscaler Acquires SPLX to Bolster AI Security Capabilities
Cloud security provider Zscaler positions itself at the forefront of defending against AI-specific threats through a strategic acquisition. The purchase of startup SPLX introduces advanced AI-driven tools designed to secure large language models and generative AI applications. This move addresses the escalating risks in AI adoption, where vulnerabilities in model training and deployment can expose enterprises to novel attack vectors.
Founded in 2023, SPLX—also known as SplxAI—specializes in runtime protection for AI systems. Its platform employs machine learning algorithms to detect anomalies in real-time during AI inference processes. The technology scans for prompt injection attacks, data exfiltration attempts, and adversarial inputs that could manipulate model outputs. SPLX’s solution integrates directly with existing AI pipelines, requiring minimal reconfiguration for cloud-native environments.
Prior to the acquisition, SPLX secured $9 million in venture funding from investors including early-stage backers focused on emerging AI risks. The startup’s team, comprising former engineers from leading AI firms, developed a proprietary risk-scoring engine that quantifies threats based on behavioral patterns. This engine assigns dynamic threat levels, enabling automated responses such as quarantine or rollback of compromised models.
Zscaler’s integration of SPLX technology expands its Zero Trust Exchange platform to include dedicated AI security modules. Customers gain visibility into AI workloads across hybrid infrastructures, with telemetry data aggregated from endpoints, networks, and cloud services. The combined system supports compliance with frameworks like NIST AI Risk Management and EU AI Act requirements for high-risk applications.
Enterprise adoption of generative AI has surged, with Gartner reporting that 80% of organizations plan to deploy AI agents by 2026. However, incidents of AI exploits have risen 45% year-over-year, according to Mandiant’s latest threat report. Zscaler’s move counters this by embedding SPLX’s defenses into its posturing engine, which prioritizes risks using context-aware analytics.
Financial terms of the deal remain undisclosed, but analysts estimate the valuation aligns with SPLX’s funding history and market traction. Zscaler, which reported $558 million in revenue for its fiscal Q1 2026, views the acquisition as accretive to its AI security segment. The company anticipates launching enhanced features in its next platform update, targeting sectors like finance and healthcare where AI governance is paramount.
This acquisition reflects a broader consolidation trend in cybersecurity, where incumbents acquire specialized AI firms to accelerate innovation. Palo Alto Networks and CrowdStrike have pursued similar strategies, snapping up observability and exposure management tools. Zscaler’s focus on runtime AI protection differentiates it, providing granular controls over model interactions without disrupting operational workflows.
For U.S. enterprises navigating AI regulations under the Biden administration’s executive orders, such integrated solutions offer audit-ready logging and bias detection mechanisms. SPLX’s algorithms also incorporate federated learning to preserve data privacy during threat intelligence sharing. As AI ecosystems mature, these capabilities will underpin secure scaling of agentic systems in production environments.
The deal closes amid heightened scrutiny of AI supply chains, following recent breaches involving third-party models. Zscaler’s CEO Jay Chaudhry emphasized the need for “invisible security” that operates seamlessly with AI acceleration hardware like NVIDIA GPUs. With SPLX’s expertise, Zscaler aims to reduce mean time to remediation for AI threats from days to minutes.
Overall, this acquisition fortifies Zscaler’s portfolio against the convergence of cloud and AI risks, positioning it to capture a share of the projected $20 billion AI cybersecurity market by 2028. Enterprises can now deploy AI with confidence, knowing defenses evolve in tandem with the technology’s rapid advancements.
