3 posts tagged with "prompt-injection"

This article assumes you're familiar with system prompts. If not, here are examples.

As AI technology advances, so must security practices. System prompts drive AI behavior, so naturally, we want these as robust as possible; enter system prompt hardening. Increased reuse of system prompts affects their prevalence, affecting the number of attacks to manipulate them.

No one would look at their AI's mangled output and decide 'Maybe the real treasure was the prompts we made along the way' with the problem being the opposite.

Let's face it - LLMs are gullible. With a few carefully chosen words, you can make even the most advanced AI models ignore their safety guardrails and do almost anything you ask.

As LLMs become increasingly integrated into apps, understanding these vulnerabilities is essential for developers and security professionals. This post examines common techniques that malicious actors use to compromise LLM systems, and more importantly, how to protect against them.

In August 2024, security researcher Johann Rehberger uncovered a critical vulnerability in Microsoft 365 Copilot: through a sophisticated prompt injection attack, he demonstrated how sensitive company data could be secretly exfiltrated.

This wasn't an isolated incident. From ChatGPT leaking information through hidden image links to Slack AI potentially exposing sensitive conversations, prompt injection attacks have emerged as a critical weak point in LLMs.

And although prompt injection has been a known issue for years, foundation labs still haven't quite been able to stamp it out, although mitigations are constantly being developed.