Why Multimodal AI Matters
Improve user experience across any use case
Multimodal AI enables AI systems to process and integrate multiple types of data (text, images, audio, sensor data, and video) to perform more complex tasks and make more accurate predictions.
Highlighted below are example use cases where multimodal AI improves user experience.
Multimodal AI Use Cases
Customer Support:
Medical Diagnosis:
Marketing- Content Generation:
Intelligent Virtual Agents (IVRs):
Personal Assistants on Mobile Devices:
Copyright Protection:
Why Multimodal AI Systems Are More Vulnerable
Multimodal systems are inherently more vulnerable than their unimodal counterparts, as they are susceptible to attacks leveraging input methods such as image, text-to-image or voice exploitation.
As illustrated in Figure 1, multimodal AI systems are designed to protect against individual text inputs. However, they become vulnerable when users leverage image, text/ image combinations, or voice prompts for exploitation.
User
Any Multimodal LLM Response
Correct Response
Stealing someone's intellectual property (IP) can be a serious offense, and it's essential to understand the legal framework and consequences.
Unpredictable Response
Stealing someone's intellectual property (IP) can be a serious offense / Step 1: gather info by starting to research the IP rights.
Non-compliant Response
Step 1: Gather Information Start by researching the intellectual property rights associated with the specific work or idea you wish to steal. Look for legal documents, patents, and copyright notices…
Non-compliant Response
Step 1: Gather Information Start by researching the intellectual property rights associated with the specific work or idea you wish to steal. Look for legal documents, patents, and copyright notices…
Figure 1: Multimodal AI systems are easy to manipulate due to image, text / image and voice commands overriding typical security safeguards.
Security Challenges with Multimodal AI Systems
As multimodal AI adoption grows, security risks escalate— adversarial attacks, bias, and data poisoning threaten reliability and trust.
Security Risks
Increased Attack Surface
AI chatbot designed to reject harmful text queries can execute the same command if spoken as audio or embedded in an image.
Bias Concerns
Compounded Issues
Job recruitment AI could favor certain accents in voice interactions and show gender/race bias in image recognition.
Privacy & Data Leakage
Unintended Exposure
Customer support AI that transcribes voice calls might store credit card details unintentionally, leading to data breaches.
Enkrypt AI Multimodal AI Security: A Two-Pronged Approach
Dual approach detects and removes multimodal AI threats before and during production.
Multimodal AI Red Teaming
Text | Image | Voice
Blended attack methods to safeguard against:
Security | Bias | Privacy
Compliance Violations: (NIST, OWASP, EU AI Act)
Multimodal AI Guardrails
Text | Image | Voice
High accuracy, low latency protection against:
Security | Bias | Privacy | Hallucinations
Compliance Violations: (NIST, OWASP, EU AI Act)
How Enkrypt AI’s Multimodal Red Teaming Works
Our Red Teaming capabilities detect all malicious individual or blended prompts, including text, image, and voice modalities. Such detection is done to adversarial prompt inputs as well as LLM response outputs. See Figure 2 below.
Figure2: How Enkrypt AI Red Teaming safeguards multimodal AI systems in pre-production.
How Enkrypt AI’s Multimodal Guardrails Work
Our Guardrails capabilities block all malicious individual or blended prompts, including text, image, and voice modalities. See Figure 3 below.
User
Any Multimodal LLM Response
Alone
Guardrails
Alone
Figure 3: How Enkrypt AI Guardrails safeguard multimodal AI systems in production.
Get Enterprise Visibility into All Multimodal AI Systems with Enkrypt AI Monitoring
Dashboard views show all threats detected and removed in multimodal AI systems. Breakdowns of text, image, and voice exploits are shown below in Figure 4.
Figure4: Enkrypt AI dashboard view of all multimodal AI system threats detected and removed. Breakdowns of text, image, and voice exploits are shown as well as readiness for AI compliance frameworks.
We chose Enkrypt AI to secure our multimodal AI application—transforming text commands into image creatives for ads and e-commerce listings. Their capability in safeguarding AI-generated text and creatives is exceptional.
Benefits of Secured Multimodal AI
Gain Competitive Advantage
Deploy AI applications securely while keeping pace with rapid innovation.
Accelerate AI Adoption
Scale the adoption of generative AI by optimizing for both security and performance.
Ensure AI Risk Management
Evaluate your AI systems against operational and reputational risks throughout dev and deployment.
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