Challenge
Artificial intelligence is a rapidly evolving technology with wide-reaching implications on security and compliance. Unfortunately for security professionals, rapid change means a seemingly infinite list of unknown risks and threats to businesses.
Between newly published or amended compliance frameworks, and new threat surfaces for attackers to exploit, organizations require a comprehensive AI strategy to address the multitude of new challenges.
Sources
State of Security 2024, Splunk.
“AI Survey Reveals AI Security and Privacy Leads to Improved ROI”, by Avivah Litan and Leinar Ramos, 14 May 2024, Gartner.
How We Support Security Leaders
We bring security expertise among a range of disciplines to help you craft a comprehensive, forward-looking strategy to address Artificial Intelligence. Our team examines the various risk and opportunities of AI, from addressing threats to your security, to identifying areas where AI implementation can elevate existing solutions.
Our compliance experts stay up-to-date with the myriad of domestic and global frameworks and standards that address AI usage. This includes:
- ISO 42001
- NIST AI Framework
- EU AI Act
- HITRUST AI Risk Management Assessment

Strategic Approach to AI Security
Step 1
AI Security Capability Assessment
Step 2
Program Development
Step 3
AI Threat Testing
Step 4
Solution Implementation

Evaluate the current organizational usage and capability in AI and LLM including:
- Define AI Use Cases
- Define Population
- Define Data Input and Output from Generative AI Tools
- Understand and Identify Risk
- Provide Recommendations for Controls
Tevora leverages industry frameworks (i.e. NIST, OWASP), security and risk best practices, and business acumen to develop best-in-industry AI Security Programs. Programs include the following:
- Policies & Procedures
- Third Party Risk Management
- Privacy, Legal & Compliance
- User Training
Ensure your organization is secure by testing your defenses before an attacker has the chance:
- Test API Integrations
- Test Retrieval Augmented Generation (RAG)
- Test Private vs. Public Hosting
- Testing for Prompt Injection
- Testing for Data Leakage, including Prompt Leaking
Identify, define requirements and implement tools to monitor or prevent LLM and Generative AI tools including:
- Data Loss Prevention
- UBE/UBA
- Security service edge (SSE) providers that can intercept web traffic to known applications
- Web Filtering
- Browser Isolation
Experts in Compliance



