Integrating LLMs (large language models) with enterprise applications enables organizations to directly embed LLMs into operations for a wide range of use cases. These integrations can create greater operational efficiencies and enhance employee productivity, unlock better data insights, improve decision-making, and gain a competitive edge. But these integrations also create certain security risks, according to BreachLock.
The key risks are data loss, prompt injection attacks, unauthorized actions, and supply chain vulnerabilities. Security teams cannot ignore the new exposure paths that LLM-app integrations introduce. Securing these integrations requires continuous validation, real-world adversarial testing, and a clear understanding of how LLM-driven workflows behave, especially under pressure in unique scenarios.
In a new blog post, the experts at BreachLock explain how organizations can adopt LLM-app integrations with more confidence and safely turn AI innovation into a competitive advantage.
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