TraceX Labs develops Vastav AI deepfake detection platform

Indian cybersecurity firm TraceX Labs has launched Vastav AI, a platform it describes as India's first enterprise-grade deepfake detection tool. The technology arrives as synthetic media increasingly fuels fraud, impersonation attacks, and large-scale misinformation campaigns across the country's digital ecosystem.

Originally developed under the company's former name, Zero Defend Security, the platform uses artificial intelligence and digital forensics to analyze images, videos, and audio for signs of manipulation. The team behind Vastav AI recently received official recognition at the CIDECODE Hackathon organized by CID Karnataka, an event focused on building technology for cybercrime investigations.

How the detection engine works

Vastav AI runs multiple layers of analysis against uploaded media files. It examines metadata, generates heatmap visualizations of manipulated regions, and applies several AI verification models to produce a confidence-based authenticity score. The platform flags AI-generated images, deepfake videos, and synthetic or cloned audio.

The system also produces investigation-ready reports. This matters for cybersecurity teams who need to document findings clearly - whether for internal audits, law enforcement referrals, or courtroom evidence chains. The interface is built for both technical analysts and non-technical users who simply need a yes/no authenticity assessment.

From hackathon recognition to enterprise deployment

The CIDECODE Hackathon, where the project gained official recognition, connected developers directly with law enforcement requirements. "The event brought together innovators and cybersecurity professionals to develop technology-driven solutions for cybercrime investigation," according to the organizers. That practical grounding shaped the platform's focus on forensic reporting and multi-model verification rather than single-algorithm detection.

TraceX Labs, which now maintains and develops the platform, specializes in threat intelligence, digital forensics, vulnerability assessment and penetration testing, cloud security, and malware research. The company's transition from Zero Defend Security reflects a broader expansion into AI-powered security products.

Where deepfake detection fits into security workflows

The platform targets several operational use cases. Cybercrime investigators can use it to verify evidence before building cases. Media organizations and fact-checking teams can screen user-submitted content for synthetic manipulation. Corporate security teams can detect deepfake audio used in CEO fraud and social engineering attacks. Government agencies gain a verification layer for intelligence gathering and digital forensics.

As generative AI tools become cheaper and more accessible, the volume of synthetic media will rise. Having verification technology integrated into standard security toolchains shifts detection from a specialized forensic task to a routine step in content intake and investigation workflows. For IT and development professionals, the arrival of enterprise-grade tools like Vastav AI signals that deepfake detection is moving from academic research into production environments - and that the skill sets around digital forensics and AI security are becoming essential rather than optional.

Professionals looking to build expertise in this area can explore structured training through the AI Learning Path for Cybersecurity Analysts, which covers the intersection of artificial intelligence and security operations. Those in broader IT roles may also find relevant coursework under AI for IT & Development.

Why this matters for IT and development professionals

Deepfake detection is no longer a niche research topic - it is becoming a standard component of security infrastructure. For developers, this means understanding how verification APIs and forensic analysis pipelines integrate into existing applications. For IT security teams, it means adding synthetic media detection to incident response playbooks and threat modeling exercises. The technology behind Vastav AI combines computer vision, audio analysis, and metadata forensics, which means cross-disciplinary knowledge in AI model evaluation and digital evidence handling will increasingly appear in job requirements and project scopes.