Ramp's Sheets AI Disclosure Shows the Growth Play: Use Responsible Security Disclosures to Build Credibility, Not Just Fix Bugs.

The Play

PromptArmor's disclosure of the Ramp Sheets AI vulnerability is not just a security fix.

It is a growth play.

The firm found a real, demonstrable flaw in a popular AI product, reported it responsibly, and published a detailed write‑up after the fix.

That sequence does three things:

1. Establishes credibility – you know what you’re talking about because you found the bug.

2. Builds trust – you helped the vendor fix it, you didn’t just leak it.

3. Creates demand – every company using similar AI now wonders if they’re vulnerable, and you’re the obvious person to ask.

That is how security research becomes a growth channel.

Why this works now

AI adoption is moving faster than AI security.

Companies are rolling out AI agents that edit spreadsheets, write code, answer support tickets, and analyze internal documents—often without a clear security review.

When a vulnerability like Ramp’s Sheets AI emerges, it triggers a broader anxiety: “What other AI tools are we using that could leak data?”

That anxiety creates a market for AI security expertise.

And the fastest way to become the expert is to publicly demonstrate that expertise on a real, high‑profile vulnerability.

What PromptArmor got right

1. They picked a high‑profile target

Ramp is a well‑known fintech company. Its Sheets AI product is a concrete example of an AI agent editing sensitive data.

2. They focused on a tangible risk

The vulnerability allowed indirect prompt injection to exfiltrate financial data via formulas. That’s easy to explain and easy to fear.

3. They followed responsible disclosure

They reported privately first, waited for the fix, then published. That builds trust with both the vendor and the market.

4. They published a detailed, educational write‑up

The post walks through the attack chain, shows proof‑of‑concept code, and includes a timeline. It’s a resource, not just a news item.

5. They tied it to a broader category

They mention a similar vulnerability in Claude for Excel, framing the issue as a category risk, not a one‑off bug.

That combination turns a single bug report into a credibility asset.

The growth play to steal

If you’re building a security, consulting, or audit business around AI, don’t wait for clients to find you.

Go find the vulnerabilities they’re afraid of, and publish the fixes.

The playbook looks like this:

1. Choose a target category

Pick an AI product category that is growing fast, handles sensitive data, and likely has security gaps. Spreadsheet AI agents, coding assistants, and knowledge‑base chatbots are good starting points.

2. Look for high‑impact, easy‑to‑demonstrate flaws

Focus on vulnerabilities that can lead to data exfiltration, unauthorized actions, or financial loss. The more tangible the risk, the stronger the story.

3. Report responsibly

Give the vendor a clear heads‑up, a reasonable deadline, and a cooperative tone. The goal is a fix, not a feud.

4. Publish a detailed write‑up

After the fix is live, publish a post that explains the vulnerability, shows how it works, and offers mitigation advice. Make it a resource the market can trust.

5. Promote where your buyers are

Share the write‑up on Hacker News, LinkedIn, Twitter, and industry newsletters. Frame it as a public service, not a sales pitch.

6. Convert interest into offers

Have a clear next step for readers who want help—an AI security audit, a vendor risk assessment, a training workshop. Turn curiosity into clients.

Why founders miss this

Because it feels indirect.

Founders often think growth means advertising, content marketing, or outbound sales. They overlook that a single, well‑executed security disclosure can do more for credibility than a year of blog posts.

The wording lesson

PromptArmor’s write‑up uses concrete, operational language:

• “A vulnerability in Ramp's Sheets AI allowed the agent to insert formulas that made external network requests without user approval”
• “Indirect prompt injection”
• “Financial data exfiltration”
• “Timeline: Feb 19, 2026 – Mar 16, 2026”

That specificity makes the threat feel real and the expertise feel genuine.

Bottom line

The Ramp Sheets AI disclosure is a case study in turning security research into growth.

Find a real vulnerability in a popular AI product, report it responsibly, publish a detailed write‑up, and position yourself as the expert for that category.

That’s how you build trust in a market that’s hungry for it.

Sources:

https://www.promptarmor.com/resources/ramps-sheets-ai-exfiltrates-financials