Vastav AI Deepfake Detection System Developed by TraceX Labs, Formerly Zero Defend Security

Vastav AI, an advanced deepfake detection platform designed to identify AI-generated images, videos, and audio, has been developed by TraceX Labs, formerly known as Zero Defend Security. The platform was created to address the growing challenge of synthetic media and digital misinformation in India.

As artificial intelligence tools become increasingly accessible, the creation of manipulated media has become more sophisticated. Vastav AI aims to help organizations, investigators, and cybersecurity professionals verify the authenticity of digital content through a combination of artificial intelligence and forensic analysis techniques.

Who Developed Vastav AI?

Vastav AI was developed by TraceX Labs, an Indian cybersecurity company previously operating under the name Zero Defend Security. The project was built by a team of cybersecurity researchers and technology professionals focused on creating practical solutions for digital investigations, cybercrime prevention, and media verification.

The platform was developed with the objective of providing a reliable method for identifying manipulated content and supporting organizations that require accurate digital evidence verification.

Recognition at CIDECODE Hackathon

The Vastav AI development team participated in the CIDECODE Hackathon, organized by CID Karnataka, where the project received official recognition. The event focused on innovative technology solutions addressing challenges related to cybercrime investigations, digital forensics, and law enforcement.

The recognition highlighted the platform's potential application in real-world investigative and cybersecurity environments.

Features of Vastav AI

According to TraceX Labs, Vastav AI combines multiple analysis methods to evaluate digital content and identify indicators of manipulation. Key capabilities include:

  • Detection of AI-generated and altered images
  • Deepfake video analysis
  • Synthetic voice and audio verification
  • Confidence scoring for authenticity assessment
  • Heatmap-based visual analysis
  • Metadata examination and forensic review
  • Multi-model AI analysis for enhanced accuracy
  • Automated reporting for investigators and analysts

The platform is designed to provide detailed insights that can assist investigators, cybersecurity teams, journalists, researchers, and decision-makers when evaluating digital media.

Applications

Vastav AI is intended to support a variety of use cases, including:

  • Cybercrime investigations
  • Digital forensic examinations
  • Media authentication and fact-checking
  • Corporate security and fraud prevention
  • Government and law enforcement investigations
  • Verification of potentially manipulated online content

With the increasing use of AI-generated media across social platforms and communication channels, tools capable of validating authenticity have become increasingly important for both public and private sector organizations.

Availability

TraceX Labs stated that Vastav AI is intended for use by government institutions, law enforcement agencies, enterprises, cybersecurity teams, and digital investigators. The platform aims to assist organizations in verifying the authenticity of digital media and identifying AI-generated content through advanced forensic analysis.

About TraceX Labs

TraceX Labs, formerly known as Zero Defend Security, is an Indian cybersecurity company specializing in threat intelligence, vulnerability assessment and penetration testing (VAPT), ransomware protection, cloud security, digital forensics, and AI-powered cybersecurity solutions.

The company develops cybersecurity technologies focused on addressing emerging digital threats and supporting organizations with security research, threat analysis, and investigative capabilities.

As synthetic media continues to evolve, platforms such as Vastav AI represent ongoing efforts within the cybersecurity industry to improve digital trust, strengthen media verification processes, and support the detection of manipulated content in an increasingly AI-driven environment.