Picture this. A term sheet lands in your inbox from the other side of the deal, and before your team reads it line by line, someone runs it through an AI tool to get a quick summary of the key terms. The summary looks clean. Valuation, liquidation preference, board seats, all accounted for. You move forward on that basis.
Now imagine that the document contained a few lines of hidden text, invisible to a human skimming the page but perfectly readable to the AI model, instructing it to leave out a clause or describe a provision differently than it actually reads. The document didn’t need to be sent in bad faith. Hidden text like this can enter a file at almost any point before it reaches you: a compromised template, a prior draft that passed through an unrelated tool, a shared drive with outdated permissions, or, yes, deliberate tampering by whoever last touched the file.
This is not science fiction. It is a known, documented risk category called prompt injection, and it currently sits at the top of the OWASP list of security risks for applications built on large language models.
Founders do not need to become AI security experts. But if AI tools are touching any part of your financing process, this is worth a few minutes of your attention.
How This Shows Up in a Financing Deal
Prompt injection works by hiding instructions inside content that an AI tool will eventually process: a PDF, a spreadsheet, an email, a data room file. When the AI reads that content, it can follow the embedded instructions instead of, or in addition to, whatever task the user actually asked it to do.
In a corporate or venture financing context, that content is everywhere. SAFEs, term sheets, subscription agreements, disclosure schedules, and cap tables move constantly between founders, investors, and their respective counsel, often through shared drives and increasingly through AI-assisted review tools. A few ways this risk can surface in practice:
- An AI-assisted contract review tool summarizing a term sheet could be manipulated to omit or misstate a material term by hidden text.
- A counterparty’s diligence response or data room file contains embedded instructions aimed at whatever AI tool is used to process it on your side.
- A CRM or deal-tracking system that automatically ingests emails and attachments processes unsanitized inputs, creating an opening most teams never think to check for.
The core risk is that any AI tool acting on a document from outside your organization inherits the trust level of whoever created that document. NIST’s AI Risk Management Framework reflects this same principle directly: its Govern function calls for policies addressing risks that arise from third-party software and data, and its Map function requires organizations to account for third-party components when identifying risks across an AI system, not just the model itself.
This Is a Legal Matter As Well As a Technical One
It is tempting to file this under IT security and move on. But the consequences land squarely in legal territory. If a manipulated AI summary leads a founder to sign a deal on terms materially different from what they believed they agreed to, that opens real questions about mistake, disclosure, and whether the resulting agreement is even enforceable as understood by both sides.
As AI tools become a standard part of transactional practice on both sides of the table, expect this issue to show up in the paperwork itself. Diligence checklists asking what AI tools were used and how, and representations addressing AI-assisted review, are likely to become a more routine feature of financing documentation rather than an afterthought.
What Founders and Deal Teams Should Do
None of this means founders should avoid AI tools in their deal process. It means treating them the same way you would treat any other assistant with limited judgment: useful for a first pass, not a substitute for careful human review.
A few concrete habits are worth adopting now:
- Treat AI-generated summaries of financing documents as a starting point, and never use them as a replacement for your attorney’s review of the underlying document itself.
- Ask your counsel and finance team which AI tools are already part of your deal process, and whether those tools have any safeguards against manipulated or adversarial inputs.
- Be especially careful with documents coming from unfamiliar counterparties before running them through AI tools, particularly tools that can edit files or take actions on their own.
- Keep a human checkpoint on anything that touches deal terms, wiring instructions, or signature blocks. No AI-generated summary should be the last set of eyes on something legally binding.
Staying Ahead of a Fast-Moving Risk
Prompt injection is still a relatively new concept for most people outside of AI security circles, but the underlying lesson is an old one dressed in new clothes: know what you are trusting, and know who controls it. As AI becomes woven into how financing deals get reviewed and negotiated, that principle applies just as much to a term sheet summary as it does to any other part of the deal.
Inventus Law works at the intersection of technology transactions and venture financing, and we are watching closely as AI tooling reshapes the risk landscape for the founders we advise.
If you have questions about how AI tools are being used in your financing process, or you would like a second set of eyes on documents before you sign, call us at (650) 843-0988 or email info@inventuslaw.com to schedule a consultation.
This article is provided for general informational purposes and does not constitute legal advice. Please consult with a licensed attorney regarding your specific circumstances.
