By Matthew Burton (Staff Software Developer), Albert Shala (Sr. Staff Software Developer), and Anurag Das (Sr. Software Developer)
Key Takeaways:
- New Trend Micro research found that while LLMs can act as automated judges for security risks, they can miss threats like hallucinated packages and can be tricked by adversarial prompts.
- These gaps could lead to data exfiltration, supply chain attacks, and operational disruptions if not addressed with proper guardrails.
- Any organization using generative AI, LLM copilots, or automated workflows is potentially at risk, especially where external code or package managers are involved.
- To reduce exposure, review LLM use, add guardrails, and validate critical outputs with external sources.
- Trend Micro offers AI Guard in Trend Vision One™, security-tuned models, and managed services to help organizations benchmark, monitor, and secure their LLM deployments.
Introduction
As large language models (LLMs) become more capable and widely adopted, the risk of unintended or adversarial outputs grows, especially within a security-sensitive context. To identify and mitigate such risks, Trend Micro researchers ran LLM…
