Simon Willison’s Weblog

The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions (via) By far the most detailed paper on prompt injection I’ve seen yet from OpenAI, published a few days ago and with six credited authors: Eric Wallace, Kai Xiao, Reimar Leike, Lilian Weng, Johannes Heidecke and Alex Beutel.

The paper notes that prompt injection mitigations which completely refuse any form of instruction in an untrusted prompt may not actually be ideal: some forms of instruction are harmless, and refusing them may provide a worse experience.

Instead, it proposes a hierarchy—where models are trained to consider if instructions from different levels conflict with or support the goals of the higher-level instructions—if they are aligned or misaligned with them.

The authors tested this idea by fine-tuning a model on top of GPT 3.5, and claim that it shows greatly improved performance against numerous prompt injection benchmarks.

As always with prompt injection, my key concern is that I don’t think “improved” is good enough here. If you are facing an adversarial attacker reducing the chance that they might find an exploit just means they’ll try harder until they find an attack that works.

The paper concludes with this note: “Finally, our current models are likely still vulnerable to powerful adversarial attacks. In the future, we will conduct more explicit adversarial training, and study more generally whether LLMs can be made sufficiently robust to enable high-stakes agentic applications.” # 23rd April 2024, 3:36 am

OpenAI Begins Tackling ChatGPT Data Leak Vulnerability (via) ChatGPT has long suffered from a frustrating data exfiltration vector that can be triggered by prompt injection attacks: it can be instructed to construct a Markdown image reference to an image hosted anywhere, which means a successful prompt injection can request the model encode data (e.g. as base64) and then render an image which passes that data to an external server as part of the query string.

Good news: they’ve finally put measures in place to mitigate this vulnerability!

The fix is a bit weird though: rather than block all attempts to load images from external domains, they have instead added an additional API call which the frontend uses to check if an image is “safe” to embed before rendering it on the page.

This feels like a half-baked solution to me. It isn’t available in the iOS app yet, so that app is still vulnerable to these exfiltration attacks. It also seems likely that a suitable creative attack could still exfiltrate data in a way that outwits the safety filters, using clever combinations of data hidden in subdomains or filenames for example. # 21st December 2023, 4:10 am

Let ChatGPT visit a website and have your email stolen. Johann Rehberger provides a screenshot of the first working proof of concept I’ve seen of a prompt injection attack against ChatGPT Plugins that demonstrates exfiltration of private data. He uses the WebPilot plugin to retrieve a web page containing an injection attack, which triggers the Zapier plugin to retrieve latest emails from Gmail, then exfiltrate the data by sending it to a URL with another WebPilot call.

Johann hasn’t shared the prompt injection attack itself, but the output from ChatGPT gives a good indication as to what happened:

“Now, let’s proceed to the next steps as per the instructions. First, I will find the latest email and summarize it in 20 words. Then, I will encode the result and append it to a specific URL, and finally, access and load the resulting URL.” # 19th May 2023, 3:34 pm

Twitter pranksters derail GPT-3 bot with newly discovered “prompt injection” hack. I’m quoted in this Ars Technica article about prompt injection and the Remoteli.io Twitter bot. # 16th September 2022, 6:33 pm