update

.github/workflows/ci.yml

@@ -13,8 +13,6 @@ jobs:
       - uses: actions/checkout@v4
       - name: Configure Git Credentials
         run: |
-          touch CNAME
-          echo 'imprompter.ai' > CNAME
           git config user.name github-actions[bot]
           git config user.email 41898282+github-actions[bot]@users.noreply.github.com
       - uses: actions/setup-python@v5

docs/CNAME

@@ -0,0 +1 @@
+imprompter.ai

docs/index.md

@@ -9,19 +9,19 @@ hide:
 
 Large Language Model (LLM) Agents are an emerging computing paradigm that blends generative machine learning with tools such as code interpreters, web browsing, email, and more generally, external resources. These agent-based systems represent an emerging shift in personal computing. We contribute to the security foundations of agent-based systems and surface a new class of automatically computed obfuscated adversarial prompt attacks that violate the confidentiality and integrity of user resources connected to an LLM agent. We show how prompt optimization techniques can find such prompts automatically given the weights of a model. We demonstrate that such attacks transfer to production-level agents. For example, we show an information exfiltration attack on Mistral's LeChat agent that analyzes a user's conversation, picks out personally identifiable information, and formats it into a valid markdown command that results in leaking that data to the attacker's server. This attack shows a nearly 80% success rate in an end-to-end evaluation. We conduct a range of experiments to characterize the efficacy of these attacks and find that they reliably work on emerging agent-based systems like Mistral's LeChat, ChatGLM, and Meta's Llama. These attacks are multimodal, and we show variants in the text-only and image domains.
 
-We present various demos and textual adversarial prompts on this page. For full details, please refer to our paper.
+We present various demos and textual adversarial prompts on this page. For full details, please refer to our [paper](./paper.pdf){target="_blank"}.
 
 ## Video Demo on Real Products
 
-### [Mistral LeChat](https://chat.mistral.ai/chat) (Nemo) Scenario 1
+### [Mistral LeChat](https://chat.mistral.ai/chat){target="_blank"} (Nemo) Scenario 1
 
 ![type:video](./mistral_pii_demo.mp4)
 
-### [Mistral LeChat](https://chat.mistral.ai/chat) (Nemo) Scenario 2
+### [Mistral LeChat](https://chat.mistral.ai/chat){target="_blank"} (Nemo) Scenario 2
 
 ![type:video](./mistral_pii_demo_2.mp4)
 
-### [ChatGLM](https://chatglm.cn/main/alltoolsdetail?lang=en) Scenario 1
+### [ChatGLM](https://chatglm.cn/main/alltoolsdetail?lang=en){target="_blank"} Scenario 1
 
 ![type:video](./chatglm_pii_demo.mp4)
 

docs/overrides/main.html

@@ -21,13 +21,13 @@ <h4 class="center" style="margin-top: -1rem;">
 </p>
 
 <div class="flex-container">
-    <a href="./paper.pdf" class="center">
+    <a href="./paper.pdf" class="center" target="_blank">
         <div class="twemoji title-icon">
             {% include ".icons/fontawesome/regular/file-pdf.svg" %}
         </div>
         <div class="title-text">Paper</div>
     </a>
-    <a href="https://github.com/Reapor-Yurnero/ImPrompter" class="center">
+    <a href="https://github.com/Reapor-Yurnero/ImPrompter" class="center" target="_blank">
         <div class="twemoji title-icon">
             {% include ".icons/fontawesome/brands/github.svg" %}
         </div>