The Unknowns of AI Adoption: What CISOs Must Confront Before It’s Too Late

AI isn’t just innovation—it’s an uncharted attack surface.

☕ Good morning, Security Gang - coffee cup cheers,

AI exploded into the enterprise before we fully understood its threat model. Boards want acceleration; vendors promise governance and “AI firewalls”; teams are wiring models into real workflows. But here’s the truth from the chair: our visibility into AI risk is incomplete, and the attack surface doesn’t look like yesterday’s IT.

Below is the real threat map, what the market actually offers today, and the CISO playbook to build resilience while we learn in motion.

🚨 The Real Threats of Enterprise AI

1) Prompt Injection & Indirect Prompt Injection

Not just “jailbreaks.” Modern attacks embed malicious instructions in the model’s context—web pages, emails, files, calendars—so the AI “pulls in” the trap on its own. Microsoft calls this indirect prompt injection and treats it with defense-in-depth (prevention, detection, impact mitigation) because it’s inherent to LLMs’ stochastic behavior. (Microsoft)

• Real world: June–Sept 2025 saw multiple disclosures around Copilot context attacks; SANS highlighted Microsoft patching related prompt-injection issues across M365 surfaces. (SANS Institute)

• Research case study: EchoLeak (CVE-2025-32711) described as a “zero-click prompt injection” path in Microsoft 365 Copilot—illustrating how a model can be compromised by simply loading poisoned context. (arXiv)

• Why it matters: Your AI that “reads” customer mailboxes, intranet wikis, or tickets can be turned into a data-exfil bot without malware ever touching an endpoint. Tenable warns these context attacks are a critical AI threat for enterprises adopting assistants across email and files. (Tenable®)