AI Application Security Testing
Confidence in the security and trustworthiness of your LLM applications starts with the Kudelski Security AI Red Team
AI Application Security Testing
Large Language Models (LLMs) such as GPT-4, BERT, Claude, and Llama present unique challenges in terms of security, safety, and privacy when implemented into applications. By and large, these challenges – and the vulnerabilities that they create – are little understood by businesses that adopt them.
Kudelski Security’s AI Application Security Testing service stands out as a distinctive and essential offering in the realm of offensive security and AI penetration testing. Our experts meticulously probe every aspect of LLM use in your business, with an aim to uncover hidden vulnerabilities and assess their potential exploitation. We go beyond mere identification, providing detailed, actionable remediation strategies that effectively mitigate risks. With Kudelski Security, you gain unparalleled insight and fortified defenses, safeguarding your AI investments against evolving threats.
Talk to usBenefits
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Create Trust in LLM-Based Applications
Increase confidence in the security and trustworthiness of LLM applications – critical for internal stakeholders as well as external customers and users.
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Reduce Risk of LLM Application Deployments
By identifying vulnerabilities that can be exploited – and addressing them – your brand and business enjoys greater protection against cyber adversaries.
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Enhance Overall Security
The insights gained from red teaming exercises allow for the implementation of strong security measures, fortifying your AI applications against real-world threats and ensuring data integrity and safety.
APPLICATION SECURITY TESTING FOR LLMs
Let us identify your vulnerabilities before your adversaries do.
AI Application Security Testing delivers a controlled engagement, clear deliverables, and well-defined phases.
Visibility and understanding
The Foundation
Testing
Offensive Security
Remediation Guidance
Ongoing Security
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Red Teaming for LLMs
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Visibility and understanding
Regular security audits will ensure ongoing protection and compliance.
We’ll also deliver a detailed report with identified risks, potential impacts, and remediation AI security strategies, including specific LLM Security Guidance and tailored risk analysis and mitigation steps for LLM-based applications.
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Visibility and understanding
The engagement starts by understanding the use case and exposure of the LLM application under test and identifying key areas of concern. We get to know the application inside out – unpacking its structure, data inputs, and outputs.
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Generate reports & enforcement strategy
Investigation Report
People
Organizations
Servers
Domain names
Social media accounts
Payment accounts
Revenue streams
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Testing
AI Application Security Testing simulates attacks and misuse scenarios to identify vulnerabilities and risks. We’ll stress test the application to see if it generates problematic outputs that compromise data privacy, component integrity, and product safety.
This testing goes further to identify vulnerabilities in the AI system infrastructure.
Continued adversarial testing identifies whether adversaries can exploit those vulnerabilities in the AI system.
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Why Kudelski Security
Frequently Asked Questions
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What is AI Application Security Testing and why is it important?
AI Application Security Testing is a security practice where experts simulate attacks on AI systems, such as LLMs, to identify vulnerabilities. It’s crucial for ensuring the security and trustworthiness of AI applications by proactively identifying and mitigating potential threats before they can be exploited. This practice helps organizations understand their security posture and improve their defensive measures.
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How does AI Application Security Testing help secure Large Language Models (LLMs)?
AI Application Security Testing probes every element of LLM applications, uncovering vulnerabilities and providing strategies for mitigating risks. This process ensures that LLMs are secure, robust, and compliant with regulatory standards. By identifying weaknesses in the application and its deployment, organizations can implement effective security measures to protect their LLM applications from potential threats and ensure their reliable operation.
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What are the benefits of AI Application Security Testing for businesses?
Benefits of AI Application Security Testing for businesses include improved security posture, proactive defense against emerging threats, risk mitigation, compliance assurance, and enhanced incident response capabilities. By identifying vulnerabilities early, organizations can prevent potential breaches and maintain trust with stakeholders. AI Application Security Testing also helps in refining security policies and practices, leading to more resilient AI systems and better overall security management.
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Why should I choose Kudelski Security for AI Application Security Testing services?
Kudelski Security combines AI expertise with extensive experience in red teaming, penetration testing, and application security. Their services are based on best practices and industry standards, providing robust security assurance. Kudelski’ Security’s comprehensive approach ensures thorough vulnerability identification and remediation, helping organizations enhance their security posture and protect their AI assets effectively.
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What industries can benefit from AI Application Security Testing services?
AI Application Security Testing is beneficial for any industry utilizing AI, particularly those with high-security needs like finance, healthcare, and technology. These industries handle sensitive data and require rigorous security measures to protect it. By employing AI Application Security Testing, organizations can identify and mitigate vulnerabilities, ensuring that their AI systems operate securely and reliably, thereby maintaining compliance with regulatory requirements and protecting stakeholder interests.
