The AI listened. To the wrong person.

August 2025. Security researcher Adam Logue asked Microsoft 365 Copilot a simple question: "Can you summarize this financial report?"

The AI assistant did what it was designed to do. It read the document. It processed the content. It followed the instructions it found.

The problem? Some of those instructions weren't from Logue. They were hidden in the document itself. And they told Copilot to do something very different than summarize.

Within seconds, Copilot had retrieved the user's recent emails, encoded them, and sent them to an external server controlled by the researcher.

No exploit code. No vulnerability to patch. No malware. Just natural language instructions that the AI couldn't distinguish from legitimate commands.

This is prompt injection. And it's fundamentally different from traditional attacks.

Here's what happened: Logue embedded malicious instructions in white text across multiple spreadsheet cells in that "financial report." When Copilot read the document to summarize it, it treated those hidden instructions as legitimate commands.

The instructions told Copilot to use its search_enterprise_emails tool to fetch recent emails, convert them to hex encoding, and generate a Mermaid diagram with a fake "login button" that would send the encoded data to an attacker-controlled server when clicked.

When the user clicked what looked like a standard document button, their email data was exfiltrated.

Microsoft's traditional security controls didn't catch it because technically nothing was broken. The AI was functioning exactly as designed—just following the wrong instructions.

Why traditional security doesn't work here:

Your firewall can't parse natural language semantics. Your intrusion detection system can't identify malicious intent embedded in conversational text. Your endpoint protection can't distinguish between legitimate AI instructions and prompt injection attacks.

The vulnerability isn't in the code. It's in how AI systems fundamentally work. LLMs process natural language instructions. They're designed to be helpful and responsive. And they struggle to distinguish between instructions from authorized users and malicious commands hidden in the content they process.

This isn't unique to Microsoft. OWASP ranks prompt injection as the #1 security risk for LLM applications. It's the most fundamental vulnerability in AI systems, and it exists because of how these models are architected.

Consider what this means for your organization: every document your AI processes is a potential attack vector. Every email it reads. Every file it summarizes. Every piece of content it analyzes. If that content can contain hidden instructions, your AI can be manipulated.

And AI systems increasingly have privileged access. They connect to email systems, databases, file storage, internal tools. A compromised AI doesn't just leak one document—it can access everything its permissions allow.

Microsoft fixed this specific vulnerability in September 2025. But the underlying problem remains.

Prompt injection isn't something you patch once and forget. New attack techniques emerge constantly. GitHub Actions, ChatGPT connectors, Salesforce Agentforce—prompt injection vulnerabilities keep appearing across every major AI platform.

Organizations need security professionals who understand these AI-specific threats. Not just general cybersecurity principles, but the unique attack vectors that only exist in AI systems.

AAISM (Advanced in AI Security Management) was designed for exactly this. Released by ISACA in August 2025, it's the first certification focused specifically on AI security management. Our recent students are among the first in the world to gain these specialized skills—joining an elite group at the forefront of this emerging field.

The certification covers three critical domains:

• AI Governance and Program Management - implementing security frameworks for AI deployments
• AI Risk Management - identifying and mitigating AI-specific threats like prompt injection
• AI Technologies and Controls - securing AI integrations and data flows

Our next AAISM bootcamp starts February 9-11, 2026.

Three days covering the AI security fundamentals that traditional certifications don't address. Real-world scenarios. Practical defenses. Strategies designed for how AI actually works.

Stay secure,
The DestCert Team

P.S. To get AAISM certified, you need to hold CISSP or CISM. Our CISM bootcamp runs February 9-12—covering information security governance, risk management, incident response, and program development. CISM focuses on security management (not technical implementation), making it the perfect foundation for AAISM's AI security management focus.
 
Can't make it to the bootcamp? Join our self-paced CISM MasterClass.