LLM safety assessment
The definitive guide on avoiding risk and abuses
The definitive guide on avoiding risk and abuses
For a year and a half, companies and individuals have rushed to share their thoughts on disruptive generative AI technologies, often glossing over specific merits and risks.
The lack of clarity around these emerging technologies has left many organisations concerned and overwhelmed, with some companies denying usage entirely. Others have permitted it to stay innovative, either allowing for restricted use or brushing off security concerns entirely.
Regardless of the stance taken, generative AI isn’t going away, but it must be implemented and utilised safely. In order for this to happen, security teams must understand how these technologies can be abused.
The rapid adoption of large language models (LLMs) has changed the threat landscape and left many security professionals concerned with expansion of the attack surface. What are the ways that this technology can be abused? Is there anything we can do to close the gaps?
This new report from Elastic Security Labs, explores the top 10 most common LLM-based attacks techniques — uncovering how LLMs can be abused and how those attacks can be mitigated.
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