The Nightfall Approach: 5 Ways Our Shadow AI Coverage Differs from Generic DLP

Everyone’s talking about Shadow AI risk. But not all coverage is created equal.

What is Shadow AI?

Shadow AI refers to the unauthorized or unmonitored use of AI tools (like ChatGPT, Copilot, Claude, and Gemini) by employees in the workplace.

It’s now one of the fastest-growing data exfiltration vectors.

Employees are pasting source code, customer or patient data, contract terms, and even M&A info into gen AI tools, often without realizing the risk. And many legacy DLP tools are still catching up.

Why Generic DLP Misses the Mark

Traditional DLP solutions weren’t designed for modern browser-based AI tools. Most of them rely on brittle signals:

• Static app allow/deny lists
• Regex-based content scanning
• Endpoint-only detection
• No insight into what was typed or pasted
• No context on where the data came from

The result? Missed incidents, false positives, and poor coverage of AI risk.

The Nightfall Difference: Shadow AI Coverage That Works

Nightfall takes a fundamentally different approach: purpose-built for the modern AI era.

Here are 5 ways our coverage stands apart:

1. Context-Aware AI Monitoring

We don’t just log “user visited chat.openai.com.”

We capture the actual content pasted, typed, or uploaded, along with the data lineage — where it originated (e.g., from a Salesforce export).

You get rich visibility into what sensitive data was shared, and why it matters.

2. Coverage Across All AI Tools

We not only offer coverage of file upload or clipboard paste to any Shadow AI tool, we offer deep prompt level scanning (i.e. typed content) for all major chatbots:

• ChatGPT
• Copilot
• Claude
• Gemini
• Perplexity
• And more!

No tuning or pre-defining app lists. Monitor new tool adoption and evolve your policies accordingly.

3. Content + Context Lineage Integration

We track clipboard and file upload events tied to sensitive content.

If a user copies PII from a contract PDF and pastes it into an AI tool, or even decides to upload the entire file, we capture:

• What was copied
• What sensitive data it contains
• Where it came from
• Where it was sent

This is true cross-surface risk tracing, not generic alerting.

4. Policy-Based Blocking (an optional feature)

Nightfall can monitor, warn, or block Shadow AI interactions based on:

• Content type (e.g., PII, source code, financials)
• Destination (e.g., ChatGPT, Claude)
• Source (e.g. Salesforce, Corporate Cloud Storage)
• User, role, or device

Flexible protection that aligns to your tolerance and needs.

5. Summarized Incidents with GenAI

Our platform generates easy to understand summaries of Shadow AI incidents using GenAI:

“Employee pasted internal roadmap containing unreleased features into ChatGPT while exploring marketing suggestions.”

In addition to the ability to view the full context, this enables faster triage and more informed responses.

The Result: Shadow AI Protection That Makes Sense

With Nightfall, you don’t have to retrofit old DLP tools to monitor new risk.

You get purpose-built protection for today’s AI landscape — real visibility, real accuracy, real-time response.

Shadow AI isn’t going away — and neither is the risk.

But with the right tooling, you can protect sensitive data without slowing innovation.

Want to see Shadow AI detection in action? Book a personalized demo with us here.