MITRE ATLAS & AIShield: How AIShield aligns with MITRE ATLAS Framework

• MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) captures the full spectrum of adversary attacks and techniques, providing users an understanding of how to safeguard their AI systems.
• MITRE ATLAScontains detailed descriptions of adversarial techniques used to compromise AI systems, strategies, and countermeasures to protect AI systems against attacks, and real-world case studies on AI system vulnerabilities and incidents.
• SecureAIx Platform from AIShield helps manage AI security risks for ML and Generative AI systems by leveraging the MITRE ATLAS framework.

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Machine learning models are vulnerable to various attacks that can compromise their security and the integrity of application systems. Threats such as data poisoning, evasion, and model extraction can undermine ML systems’ security. MITRE, among other organizations, is at the forefront of educating the public about these threats and developing innovative defenses.

MITRE is a not-for-profit organization that provides solutions enhancing national security and improving people’s lives. Sponsored by the US government and private companies across various industries, including cybersecurity, MITRE is well-known for its acclaimed MITRE ATT&CK framework — a comprehensive, living knowledge base for modeling, detecting, preventing, and combating cybersecurity threats.

MITRE ATT&CK details cybercriminal tactics, techniques, and procedures (TTPs) at each phase of the cybersecurity lifecycle, helping teams simulate attacks, improve security policies, and configure security technologies. MITRE oversees several prominent cybersecurity projects, including:

• The Common Vulnerabilities and Exposures (CVE) program, which identifies and monitors software vulnerabilities, widely used by Vulnerability Management products.
• The MITRE ATT&CK (Adversarial Tactics, Techniques, and Common Knowledge) framework, which details the various stages of traditional endpoint attack tactics and techniques and is adopted by Endpoint Detection & Response (EDR) products.

Now, MITRE is focusing on machine learning system threats with MITRE ATLAS, a knowledge base of adversarial machine learning tactics and techniques. Released in June 2021, MITRE ATLAS is modeled after the ATT&CK framework, providing insights into mitigating risks associated with AI-enabled systems. It is a knowledge base of adversarial machine learning tactics, techniques, and case studies designed to help cybersecurity professionals, data scientists, and their companies stay up to date on the latest attacks and defenses against adversarial machine learning. It is a knowledge base that covers all existing adversary attacks and techniques, keeping users in the loop about the latest threats and vulnerabilities.

The ATLAS matrix systematically arranges tactics and techniques to provide a comprehensive view of the adversarial threat landscape. It catalogs the attack techniques in columns from left to right. The order of the tactics reflects the likely sequence an attacker would follow during an attack targeted at an ML system.

Underneath each tactic, there is a list of techniques (including sub-techniques) that the attacker could use to accomplish their objective. These techniques provide insight into the “how” of an attacker’s tactical approach. This list is updated as adversaries develop new attacks and researchers discover them in real-world situations.

Within the detailed information for each MITRE ATLAS technique, there are links to numerous real-world and academic examples of those techniques. Individual case studies reveal the victims of an attack, providing a mapping to various techniques observed throughout the attack.

MITRE ATLAS provides a framework for identifying and addressing vulnerabilities in AI systems, which can help to prevent attacks and protect model and sensitive data. Security professionals use MITRE ATLAS to enhance AI security practices. Developers apply best practices to secure AI models and deployments. Researchers dive into adversary tactics and contribute to the knowledge base.

Implementing MITRE ATLAS requires careful consideration of the data and the requirements of the AI system. Here are some best practices for using MITRE ATLAS in AI and LLM security:

• Define Threat Scenarios: Identify potential attackers, their motivations, and possible attack types before implementing MITRE ATLAS.
• Use Realistic Data: Simulate attacks using realistic data to ensure accurate and relevant results.
• Test Regularly: Conduct regular tests with MITRE ATLAS to detect new vulnerabilities and weaknesses as the AI system evolves.
• Involve Security Experts: Engage security experts familiar with the latest attack techniques and security practices to ensure effective and accurate assessments.

MITRE ATLAS is a powerful resource for understanding and safeguarding AI systems. It provides a comprehensive framework for identifying and addressing vulnerabilities in AI systems, which can help to prevent attacks and protect sensitive data. By understanding how MITRE ATLAS works and its applications in AI and LLM security, organizations can build more secure and resilient AI systems. Implementing best practices for using MITRE ATLAS can help to ensure that AI systems remain secure over time and comply with regulatory requirements.

The SecureAIx Platform from AIShield is tailored for safeguarding ML and Generative AI (GenAI) systems against attacks. Since inception, the platform has been designed and developed with MITRE ATLAS in mind. AIShield’s CEO & CTO Manojkumar Parmar is a founding member of MITRE ATLAS.

Below is a snapshot of the extensive coverage of AIShield’s offerings in alignment with MITRE ATLAS techniques and tactics.

AISpectra module of the SecureAIx platform offers dynamic and interactive application security (DAST and IAST) approach, ensuring vulnerabilities are identified and rectified in real-time. It comprehensively assesses the vulnerabilities of ML models. Its threat detections are mapped to MITRE ATLAS technique IDs, providing context to model and data teams understand the possible motives, current stage and to better understand the active threat and design the most appropriate response to defend against it.

This platform offers a wide range of integrations with SIEM/SOAR (such as Sentinel, Splunk, IBM QRadar, Amazon Security Lake) thereby offering a proactive defense stance that is essential for maintaining the integrity and reliability of machine learning operations. In essence, SecureAIx Platform provides a sophisticated toolset that not only addresses current security needs but also adapts to evolving threats, ensuring that your ML models operate securely and efficiently in increasingly complex environments.

For Chief Data Officers and Data Science teams, the challenges and attacks targeting machine learning models and intellectual property can complicate tasks and distract from the objective of creating improved versions of your ML models. MITRE ATLAS serves as a knowledge repository and detailed inventory of vulnerabilities in ML models that adversaries could exploit, enabling proactive security measures during development and continuous monitoring in production. MITRE ATLAS connects the realms of cybersecurity and data science, providing a shared framework and language to discuss and formulate strategies to safeguard and maintain our unique AI competitive edge. AIShield offers you the tools that you need to cover against different MITRE ATLAS attacks and techniques. AIShield is an advanced security solution that provides proactive measures to prevent and address AI security risks from the early stages of development to deployment, ensuring that AI systems stay resilient against adversarial manipulation. By offering a self-serve model, AIShield enables organizations to autonomously detect, protect, and defend their AI-based workloads across various environments, such as cloud and edge computing.

Ready to fortify your AI systems against adversarial threats? Discover how MITRE ATLAS and AIShield’s SecureAIx Platform can revolutionize your approach to AI security. Don’t wait until an attack happens — proactively protect your models today. Request a Trial or Contact Us now to learn how our advanced solutions can help you stay ahead of threats and ensure the integrity and reliability of your AI operations.