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Repello AI
Secure your AI. Outsmart Attackers.

What is Repello AI?

Repello AI offers a comprehensive solution designed to secure Generative AI (GenAI) applications against evolving cyber threats. It functions by continuously identifying, measuring, and mitigating risks associated with GenAI, such as prompt injection, jailbreak attempts, brand reputation damage, and inappropriate content generation. The platform provides ongoing monitoring and automated AI red-teaming capabilities to test AI applications from an attacker's perspective, without needing access to underlying algorithms or code (blackbox testing).

By integrating directly into CI/CD pipelines, Repello AI enables early vulnerability detection and remediation, ensuring secure deployments. It delivers comprehensive reports detailing vulnerabilities, failure modes, and actionable mitigation strategies, benchmarked against global AI security and safety standards. The service is model-agnostic, supports multimodality (text, image, audio, video), and is tailored to specific business use cases through context-aware technology, helping AI teams innovate confidently while staying ahead of potential exploits.

Features

  • Continuous AI Security: Provides ongoing monitoring and threat mitigation for GenAI applications in real-time.
  • Automated AI Red-Teaming: Tests AI applications from an attacker's perspective to identify vulnerabilities.
  • CI/CD Integration: Integrates security features directly into development pipelines for early detection.
  • Context-Aware Tailoring: Adapts security measures to the specific needs and use case of the GenAI application.
  • Comprehensive Reporting: Delivers detailed reports on vulnerabilities, failure modes, and mitigation steps.
  • Blackbox Testing: Simulates real attacks without requiring access to underlying algorithms or code.
  • Broad Vulnerability Coverage: Safeguards against over 270 vulnerability types.
  • Model Agnostic & Multimodal Support: Compatible with various AI models and supports text, image, audio, and video modalities.
  • AI Security Framework Mapping: Benchmarks application security against global AI security and safety standards.

Use Cases

  • Securing Generative AI applications against novel risks.
  • Protecting against prompt injection attacks.
  • Preventing jailbreak attempts on AI models.
  • Mitigating risks of brand reputation damage via AI misuse.
  • Blocking inappropriate or harmful content generation.
  • Continuously assessing and managing AI security posture.
  • Integrating AI security testing into the development lifecycle (CI/CD).

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