AI’s New Rule: Least Privilege or Bust

For years, Cybersecurity has lived by a golden rule: Least Privilege. No user, system, or process should have more access than absolutely necessary.

Now, as AI systems integrate deeper into our workflows pulling from external tools, calling APIs, browsing the web, even executing actions on our behalf we’re seeing why this principle matters more than ever.

Google’s Warning: Indirect Prompt Injection (IPI)

Recently, Google issued a stark warning about a rising AI risk: Indirect Prompt Injection attacks.

Unlike direct prompt injections (where attackers manipulate the AI with a cleverly worded prompt), IPI works silently in the background. Attackers embed malicious instructions into data sources a web page, a PDF, an email, even a calendar entry.

When the AI fetches that data, it unknowingly executes the hidden command. Think about it:

• A harmless-looking document could instruct your AI assistant to exfiltrate sensitive emails.

• A web search result might tell the AI to hand over your API keys.

• A calendar invite could force the AI to download malware links.

The AI isn’t "hacked" in the traditional sense, it’s simply doing exactly what it was told.

This is why Google’s warning matters. IPIs exploit the trust we place in AI to act on data without verifying the source or intent.

The Governance Blind Spot

In cybersecurity, we’ve long relied on the Principle of Least Privilege:

Give humans and systems only the access they need, nothing more.

But with AI, we’ve often abandoned this principle. Many organizations allow their AI systems to:

• Call multiple external APIs

• Access emails, documents, or customer data without boundaries

• Execute actions automatically, without human verification

This is exactly what makes Indirect Prompt Injections so dangerous. A poisoned source can manipulate an over-empowered AI into performing unauthorized or even harmful actions.

AI Governance Through Least Privilege

This is where AI Governance must step in. Extending Least Privilege to AI means:

🔹 Restrict AI capabilities → Don’t allow an AI agent to read, write, or execute across systems unless absolutely required.

🔹 Segregate access levels → Separate what AI can “see” (data inputs) from what it can “do” (system actions).

🔹 Introduce human-in-the-loop → Require approvals for sensitive actions like payments, data sharing, or configuration changes.

🔹 Audit and monitor → Treat AI like any privileged account, with full logging, review, and anomaly detection.

🔹 Guardrails for integrations → Carefully control API permissions so that one poisoned instruction doesn’t cascade across systems.

The Big Shift

Indirect Prompt Injections reveal a truth: AI doesn’t need to be hacked, it just needs to be persuaded.

That’s why AI Governance is not just about fairness, ethics, or bias. It’s also about Cybersecurity at the core making sure our AI systems don’t blindly overstep their boundaries.

The principle is timeless:

• Yesterday, we applied Least Privilege to people.

• Today, we must apply it to AI.

Because in the end, the strongest AI isn’t the one with unlimited power. It’s the one with disciplined power.

👉 What do you think, are organizations treating their AI systems with the same discipline as their human users?

Note: Above compilation is for educational purposes only, all rights remain with the OEM and used here for references with due credit.