AI can be a valuable asset, only when it’s fed with highest quality data.
Our sandbox-based analysis produces deterministic verdicts, structured indicators, and clarity your AI-powered security initiatives need for safer automation at scale, faster response, and reliable threat intelligence.
Automation runs on facts; triage time drops. Sandbox-verified behavior and IOCs your models can trust.
Behavioral truth sharpens model outcomes and rule precision. Evasion-resistant detonation produces first-order, machine-readable artifacts.
High-throughput sandboxing supplies the data volume AI needs — without noise. JSON/STIX exports mapped to MITRE for immediate ML and TIP integration.
From false positives to false confidence — the hidden AI risk
85% of AI initiatives may fail due to poor data quality and inadequate volume
CTO Magazine
96% of U.S. data professionals believe that poor AI data quality could lead to widespread crises – when data quality is not prioritized
“ The potential of artificial intelligence(AI) hinges on high-quality, first-order data. Without robust data collection, promises of transformative AI solutions remain empty. ”
World Economic Forum
AI multiplies outputs — and it multiplies mistakes if the inputs are weak.
Feed models first-order fact-based data from sandbox detonation.
Fewer false positives, faster response, confident automation.
Automation-safe verdicts lower analyst triage hours.
Full execution timelines and config extraction accelerate root-cause analysis.
Reusable, high-fidelity IOCs for TIPs and cross-agency sharing.
Clean inputs mitigate the impacts of hallucination and manual overrides.
Learn how VMRay helps organizations feed AI and automation with fact-based sandbox data and intelligence.
AI systems rely entirely on the data they are trained and fed. In cybersecurity, low-quality or noisy data leads to false positives, missed threats, and unreliable automation. High-quality, verified data ensures AI models produce accurate, actionable results that security teams can trust.
Trustworthy data is accurate, validated, and derived from real threat behavior rather than assumptions or static indicators. It should include clear context, structured outputs, and minimal duplication or noise so AI models can make reliable decisions.
VMRay generates data through dynamic malware analysis in its sandbox environment. By observing real execution behavior, it produces deterministic verdicts, structured indicators, and machine-readable outputs that provide accurate, high-fidelity inputs for AI systems.
Sandbox analysis captures how malware actually behaves in a controlled environment. This produces richer and more reliable data than static analysis, enabling AI models to detect threats more accurately and reduce both false positives and false negatives.
By providing verified, behavior-based analysis and high-confidence indicators, VMRay helps eliminate ambiguous or low-quality signals. This allows AI systems to make clearer distinctions between benign and malicious activity, reducing false positives.
VMRay delivers structured, machine-readable outputs that integrate with SIEM, SOAR, and TIP platforms. Because the data is derived from real malware behavior and validated for accuracy, organizations can confidently automate detection and response workflows.
Why sandboxing matters now more than ever in times of AI
