Secure Your AI
AI Security
Your employees are already using AI tools — whether IT approved them or not. And your AI infrastructure is being targeted by a new class of attacks your existing security stack wasn't designed to stop.
AI adoption is accelerating faster than security teams can respond. Shadow AI, prompt injection, model poisoning, and data exfiltration through LLM interfaces are real, active threats. The organizations that secure their AI transformation now will have a significant advantage over those that react after an incident.
The AI Security Risks Most Organizations Are Ignoring
- Shadow AI — employees using unauthorized AI tools — is exposing sensitive data to third-party models without organizational oversight.
- Prompt injection attacks allow adversaries to manipulate AI model outputs, bypass controls, and exfiltrate data through seemingly legitimate interactions.
- Model poisoning attacks corrupt the training data or fine-tuning process, causing AI systems to produce biased, harmful, or attacker-controlled outputs.
- AI-generated content is being used to accelerate phishing, social engineering, and deepfake attacks at scale against your organization.
- Regulatory frameworks are beginning to require AI governance documentation — organizations without it face increasing compliance exposure.
Why The Teneo Group
End-to-End Security for Your AI Transformation
The Teneo Group secures every layer of your AI environment — from the tools your users interact with daily to the infrastructure your models run on. We provide DLP protections at the prompt level, visibility into AI tool usage across your organization, and hardening of your AI infrastructure against model-layer attacks. Our approach is grounded in the NIST AI Risk Management Framework and informed by the latest threat intelligence on AI-targeted attack techniques.
The Process
How We Secure Your AI Environment
AI Risk Assessment
We discover all AI tools in use across your organization — sanctioned and unsanctioned — and assess your AI infrastructure for prompt injection vulnerabilities, data exfiltration risks, and model security gaps.
Controls Implementation
We implement DLP protections at the prompt level, establish AI usage policies, and deploy controls that prevent sensitive data from leaving your environment through AI interfaces — without blocking legitimate productivity.
Ongoing Governance
We establish an AI security governance program that monitors for new AI tool adoption, tracks policy compliance, and keeps your controls current as the AI threat landscape evolves.
The Outcome
What Secured AI Adoption Looks Like
- Full visibility into every AI tool your organization is using — approved and unapproved.
- DLP controls at the prompt level that prevent sensitive data from reaching unauthorized AI models.
- AI infrastructure hardened against prompt injection, model poisoning, and data exfiltration.
- An AI governance framework that satisfies emerging regulatory requirements.
- Confident AI adoption — your teams can leverage AI productivity tools without creating new security exposure.
Common Questions
Frequently Asked Questions
What is Shadow AI?
Shadow AI refers to AI tools and services that employees use without IT or security team approval — ChatGPT, Copilot, Gemini, and hundreds of other tools that may be processing your sensitive data on third-party infrastructure without your knowledge or consent.
What is a prompt injection attack?
Prompt injection is an attack technique where an adversary crafts malicious input that causes an AI model to ignore its instructions, reveal sensitive information, or perform unintended actions. It's the AI equivalent of SQL injection — and it's actively being exploited.
How do you implement DLP at the prompt level?
We deploy controls that inspect the content of AI prompts before they leave your environment — identifying and blocking sensitive data patterns (PII, financial data, IP) from being submitted to external AI models, while allowing legitimate usage to continue.
Do you secure AI models we build internally?
Yes. We assess internally developed and fine-tuned models for training data poisoning risks, model inversion vulnerabilities, and inference-time attack surfaces — and provide hardening recommendations aligned to the NIST AI Risk Management Framework.
What regulations apply to AI security?
The EU AI Act, NIST AI RMF, and emerging SEC guidance on AI risk disclosure are the primary frameworks. Additionally, existing data protection regulations (GDPR, HIPAA, CCPA) apply to data processed by AI systems. We help you navigate all of them.
Can you help us build an AI acceptable use policy?
Yes. We develop AI governance documentation including acceptable use policies, data classification guidelines for AI inputs, and vendor assessment frameworks for evaluating third-party AI tools — all tailored to your industry and regulatory environment.
Ready to Get Started?
Schedule a no-obligation conversation with a Teneo Group engineer. We'll assess your current environment and show you exactly where your exposure lies.