As organizations embrace generative AI to automate decisions, enhance service delivery, and optimize data management, they also are encountering a new breed of cyber threats that exploit the intelligence of these systems. One of the most concerning of these threats is the prompt injection attack, which uses language itself to manipulate AI behavior and compromise trust.
When Intelligence Becomes an Attack Surface
A prompt injection attack manipulates the instructions an AI system receives. It convinces the system to act against its original intent by embedding hidden or deceptive commands in prompts, documents, or even the external data the AI processes. This form of attack is particularly dangerous because it does not rely on traditional code exploits. Instead, it uses words to corrupt outcomes.
Imagine a generative AI tool in a customer service setting being tricked into revealing confidential data or changing workflows. In another case, an attacker might hide malicious instructions in a supplier document, causing an AI-enabled system to misroute shipments or alter invoices. These scenarios show how the language interface of AI systems has become a new and often overlooked attack surface.
Industries such as healthcare, finance, and manufacturing already are seeing examples of these tactics. Hidden instructions in data, emails, or forms can quietly override security protocols. The result is not only data exposure but also operational disruption.
The Intersection of AI Vulnerability and Cyber Resiliency
Cybersecurity teams have spent decades hardening networks, encrypting data, and deploying layered defenses. AI introduces a different challenge. These systems do not just store information; they interpret it. When an AI model is compromised, the damage extends beyond data loss. It can impact the accuracy and reliability of automated decisions that influence entire business processes.
This is why cyber resiliency has become essential. True resilience is not only about blocking attacks but also about being able to withstand and recover from them. For AI, resiliency means detecting manipulation early, isolating affected systems, and restoring normal function before significant harm occurs.
Commvault’s approach to cyber resiliency is to help organizations build for this reality. By combining data protection, threat detection, and orchestrated recovery, organizations can maintain data integrity and business continuity even when AI systems are targeted. Commvault’s goal is to provide organizations with the tools to make data not just secure, but verifiably trustworthy and recoverable.
Recognizing the Signs of Prompt Injection
The first step in building resilience is recognizing when a prompt injection might be happening. Common warning signs include:
- Instruction overrides: Prompts that include phrases like “ignore previous instructions” or “reveal hidden data.”
- Context switching: Sudden topic changes that move the AI system away from its intended purpose.
- Encoded or multilingual text: Hidden characters, encoding schemes, or foreign-language commands designed to evade detection.
- Social engineering tactics: Inputs that appear to come from an authority figure or system administrator.
Organizations should monitor AI behavior over time, establishing a baseline for what “normal” looks like. Deviations from expected responses can reveal manipulation attempts before they cause harm.
Defense in Depth: Applying Zero-Trust Principles to AI
Protecting AI systems requires the same layered mindset that has proven effective in broader cybersecurity. Zero-trust principles can apply here as well, but with added emphasis on input and output control.
- Validate inputs and outputs. Sanitize prompts before they are processed and review AI-generated responses for unexpected instructions or disclosures.
- Segment AI environments. Separate systems that process sensitive information from those that interact with untrusted data sources.
- Limit permissions. Use role-based access controls so that even if a model is tricked, it cannot access or modify critical systems.
- Continuously monitor behavior. Track AI responses over time to detect patterns that differ from expected norms.
Commvault’s ThreatWise technology can be incorporated as part of an organization’s layered protection. It detects unusual activity across AI data pipelines and flags behaviors that may signal an injection attempt. When combined with other Commvault offerings, such as Commvault Cloud, organizations can integrate early-warning detection with rapid recovery and unified visibility across hybrid environments.
AI Security and the Human Element
Technology alone cannot solve this problem. Many prompt injection attempts succeed through social engineering rather than technical exploits. They rely on human trust. Employees who use generative AI tools must understand that every prompt, file, or link can become a potential attack vector.
Regular training and simulated attack exercises can strengthen awareness. When users know what suspicious inputs look like, they become an active layer of defense rather than a weak point in the chain.
Building Trustworthy AI Through Resilient Data Practices
AI can be seen as an extension of enterprise data systems, not a separate domain, and Commvault can help customers navigate how to protect their AI. Protecting AI begins with protecting the data it learns from and the outputs it produces. That means keeping datasets, models, and metadata uncompromised, auditable, and recoverable.
Resilience must be designed into the system from the start. Whether the threat is ransomware, insider misuse, or a sophisticated prompt injection, the objective remains the same: preserve data integrity and operational availability.
AI is transforming how organizations handle information, but the foundations of cybersecurity still hold true. Data protection, ongoing monitoring, and rapid recovery remain the pillars of resilience in an increasingly intelligent world.
Final Thought
Prompt injection attacks are a reminder that innovation and risk evolve together. As enterprises accelerate their use of AI, they also must evolve their defenses. By embedding cyber resiliency into every layer of AI-supported operations, organizations can adopt new technologies with confidence, knowing that their data and decisions remain secure and reliable.
Chris DiRado is Principal Technologist, Product Experience, at Commvault.
