Generative AI is threaded through almost every enterprise workflow today — from daily tasks like asking ChatGPT a question, to powerful copilots embedded in SaaS like Microsoft 365, Salesforce, or Slack. That convenience creates a new attack surface: malicious prompt injections (MPIs).
MPIs trick AI systems into ignoring rules, running hidden code, or leaking data.
- OWASP ranks prompt injection as LLM risk #1, explicitly calling out both direct (browser input) and indirect (file/website content) vectors.
- In 2024, researchers showed Slack AI could be forced to leak data from private channels with nothing more than a poisoned prompt.
- Just last week, CrowdStrike announced a $260M acquisition of Pangea, citing AI-layer security as a board-level priority.
- A 2025 study found 4% of AI prompts and over 20% of uploaded files contained sensitive data.
If your employees are using AI, malicious code insertion is a serious risk for your organization. Learn how Polymer can protect you from this.
Why legacy tools fall short
Traditional DLP and DSPM were built for file movement and storage risk. They don’t see what’s happening inside an AI prompt — whether that’s:
- A ChatGPT or Gemini tab in the browser where a user pastes sensitive code.
- A Copilot sidebar inside Word or Slack AI query pulling from enterprise data.
- A poisoned file (CSV, PDF) embedding hidden instructions.
Without runtime controls, enterprises are blind to these risks until after data is leaked or commands are executed.
How Polymer stops prompt injection in real time
Polymer embeds identity-aware policies into both:
- Browser-based AI assistants (ChatGPT, Gemini, Anthropic, etc.)
- Embedded SaaS AI copilots (Microsoft Copilot, Google Gemini inside Docs/Sheets/Gmail, Salesforce Einstein, Slack AI).
In the browser, Polymer scans every interaction in real time, catching override language, code snippets, and exfil attempts. In embedded AI, the same guardrails apply to copilots inside SaaS — blocking or redacting malicious instructions before they touch enterprise data. Polymer also offers file-layer defense. Malicious instructions hidden inside PDFs, CSVs, or slide notes are detected before copilots or browser-based assistants process them.
Humans are still the weakest link—Polymer’s human risk management is unparalleled
Even with airtight AI guardrails, risk often starts with people:
- An employee pasting secrets into ChatGPT.
- A manager asking Copilot to “summarize sensitive emails.”
- A contractor uploading a CSV with embedded payloads into Gemini.
Polymer adds human-in-the-loop risk management on top: Live alerts to SOC analysts and managers when policy violations occur, context-rich notifications (who, what, where, what was blocked/redacted), and adaptive nudges to train employees in safer AI use without slowing workflows.
Prompt injections are already leaking data — in browser-based assistants like ChatGPT/Gemini and embedded copilots in SaaS. Attackers don’t care which surface you use; they just want the override.
Polymer’s identity-aware runtime security keeps both environments safe — blocking, redacting, and escalating as needed so enterprises can scale AI adoption without scaling risk.
Ready to see it in action? Get a demo of Polymer SecureRAG and discover how to make AI work for your business—securely, responsibly, and at scale.
