Key Takeaways
- We took a deep dive into the concept of Prompt Leakage (PLeak) by developing strings for jailbreaking system prompts, exploring its transferability, and evaluating it through a guardrail system. PLeak could allow attackers to exploit system weaknesses, which could lead to the exposure of sensitive data such as trade secrets.
- Organizations that are currently incorporating or are considering the use of large language models (LLMs) in their workflows must heighten their vigilance against prompt leaking attacks.
- Adversarial training and prompt classifier creation are some steps companies can take to proactively secure their systems. Companies can also consider taking advantage of solutions like Trend Vision One™ – Zero Trust Secure Access (ZTSA) to avoid potential sensitive data leakage or unsecure outputs in cloud services. The solution can also deal with GenAI system risks and attacks against AI models.
In the second article of our series on attacking artificial intelligence (AI), let us explore an algorithmic technique designed to induce system prompt leakage in LLMs, which is called PLeak.
System Prompt Leakage pertains to the risk that preset system…
