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Product Integrity Risk Assessment GenAI Application Security Assessment

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Product Integrity Risk Assessment

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Overview
Differentiators
Features
Overview
Differentiators
Features

Solution Overview

EPAM’s GenAI Security Product Integrity Risk Assessment helps enterprises improve the security of their GenAI applications by identifying vulnerabilities and providing a clear plan for AI-enabled security. The process includes a detailed review of the architecture and key protections such as data encryption, user authentication, modular design, and real-time monitoring for unusual activity. It also addresses AI-specific risks like model poisoning, prompt injection attacks, and API abuse, which are unique to AI-driven systems.

Our assessment delivers practical recommendations to reduce risks and proposes design improvements based on best practices to strengthen security controls. With EPAM’s GenAI Security Product Integrity Risk Assessment, clients can proactively protect their GenAI solutions against emerging and advanced cybersecurity threats.

Customer Problem

  • LLMs bring a new set of security risks that require fresh approaches to testing and defense  

  • Models and ingested data became an additional asset to protect and underlying infrastructure increased attack surfaces  

  • Attack techniques like prompt injection remain unresolved on a fundamental level, making it difficult to fully secure these systems  

  • The unpredictable nature and complexity of LLMs make traditional security testing methodologies less effective, requiring new approaches 

  • LLM architectures are still evolving, and security measures for them are not yet mature or standardized  

  • It’s not just malicious actors who can manipulate LLMs – everyday users without technical skills can also cause unintended or harmful behaviors. 

EPAM Solution

Integrating the Product Integrity Risk Assessment early in the development process empowers clients to build applications that are resilient, compliant, and trustworthy. EPAM’s dedicated team of security experts and data scientists provides comprehensive testing and risk analysis, addressing both architectural design and implementation phases. This strategic approach, combined with deep engineering expertise, not only reduces risks but also promotes innovation. The result is enhanced long-term credibility and reliability for our clients’ solutions. 

  • Addressing Security Gaps in AI Deployments:
    EPAM's solution identifies and mitigates vulnerabilities unique to LLM-based solutions, ensuring robust and secure deployments tailored specifically for AI systems.

  • Avoiding Late-Stage Fixes:
    By proactively integrating security measures early in the AI lifecycle, EPAM minimizes costly and disruptive last-minute overhauls, allowing for more predictable and efficient project execution.

  • Bridging AI Expertise Gaps:
    EPAM combines the knowledge of security specialists and data scientists to enhance interdisciplinary collaboration, bridging the divide between AI development and security expertise.

  • Navigating Complex Compliance:
    EPAM ensures alignment with evolving regulatory requirements, Responsible AI principles, and data privacy standards, helping businesses meet compliance effortlessly while maintaining trust.

*If a client would like to train their security team on this subject, we can also offer training or a workshop, hands-on 1-2 days of training, remote or on-site. 

Key Differentiators

Comprehensive Risk Awareness

Provides a full-spectrum view of GenAI threats, covering design, runtime, and unpredictable application behavior.

Streamlined Integration

Embeds security directly into architecture, code, and CI/CD pipelines for seamless implementation.

Benefits

Risk-Driven Prioritization

Focus on critical threats, reducing costs from breaches and regulatory penalties

Faster Time to Market

Accelerate AI innovation securely, avoiding delays and maintaining momentum.

Competitive Edge

Build trust by meeting GenAI security standards and staying ahead of competitors

Cost Efficiency

Lower costs by addressing vulnerabilities early, proactive security assessments

Proactive Security by Design

Integrate security early to minimize rework and boost development speed

Actionable Insights

Provides recommendations to mitigate risks and enhance LLM security.

Features

  • 360-Degree Risk Assessment: Offers a comprehensive evaluation of risks impacting the security, reliability, performance, and integrity of LLM-enabled products.

  • Multi-Layered Security Approach: Tackles AI security challenges through a holistic methodology, including architecture and LLM pipeline analysis, penetration testing, configuration review, threat modeling, and conversational performance evaluation (e.g., content reliability).

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