deploy: 22bc3d2798

guides/prompt_guard.html

@@ -169,8 +169,7 @@ By adding a layer of input scrutiny, prompt guard ensures safer, more reliable,
 </li>
 <li><dl class="simple">
 <dt><strong>Prompt Sanitization</strong></dt><dd><ul>
-<li><p><strong>Injection Prevention</strong>: Detects and filters inputs that might attempt injection attacks, like adding code or SQL queries in a prompt-based application.</p></li>
+<li><p><strong>Jailbreak Prevention</strong>: Detects and filters inputs that might attempt jailbreak attacks, like alternating LLM intended behavior, exposing the system prompt, or bypassing ethnics safety.</p></li>
-<li><p><strong>Content Filtering</strong>: Identifies and removes potentially harmful, sensitive, or inappropriate content from inputs to maintain safe interactions.</p></li>
 </ul>
 </dd>
 </dl>
@@ -178,7 +177,6 @@ By adding a layer of input scrutiny, prompt guard ensures safer, more reliable,
 <li><dl class="simple">
 <dt><strong>Intent Detection</strong></dt><dd><ul>
 <li><p><strong>Behavioral Analysis</strong>: Analyzes prompt intent to detect if the input aligns with the function’s intended use. This can help prevent unwanted behavior, such as attempts to bypass limitations or misuse system functions.</p></li>
-<li><p><strong>Sentiment and Tone Checking</strong>: Examines the tone of prompts to ensure they align with application guidelines, useful in conversational systems and customer support interactions.</p></li>
 </ul>
 </dd>
 </dl>
@@ -209,7 +207,7 @@ Arch-Guard is designed to address this challenge.</p>
 <section id="what-is-arch-guard">
 <h3>What Is Arch-Guard<a @click.prevent="window.navigator.clipboard.writeText($el.href); $el.setAttribute('data-tooltip', 'Copied!'); setTimeout(() =&gt; $el.setAttribute('data-tooltip', 'Copy link to this element'), 2000)" aria-label="Copy link to this element" class="headerlink" data-tooltip="Copy link to this element" href="#what-is-arch-guard" x-intersect.margin.0%.0%.-70%.0%="activeSection = '#what-is-arch-guard'"><svg height="1em" viewbox="0 0 24 24" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M3.9 12c0-1.71 1.39-3.1 3.1-3.1h4V7H7c-2.76 0-5 2.24-5 5s2.24 5 5 5h4v-1.9H7c-1.71 0-3.1-1.39-3.1-3.1zM8 13h8v-2H8v2zm9-6h-4v1.9h4c1.71 0 3.1 1.39 3.1 3.1s-1.39 3.1-3.1 3.1h-4V17h4c2.76 0 5-2.24 5-5s-2.24-5-5-5z"></path></svg></a></h3>
 <p><a class="reference external" href="https://huggingface.co/collections/katanemolabs/arch-guard-6702bdc08b889e4bce8f446d" rel="nofollow noopener">Arch-Guard<svg fill="currentColor" height="1em" stroke="none" viewbox="0 96 960 960" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M188 868q-11-11-11-28t11-28l436-436H400q-17 0-28.5-11.5T360 336q0-17 11.5-28.5T400 296h320q17 0 28.5 11.5T760 336v320q0 17-11.5 28.5T720 696q-17 0-28.5-11.5T680 656V432L244 868q-11 11-28 11t-28-11Z"></path></svg></a> is a robust classifier model specifically trained on a diverse corpus of prompt attacks.
-It excels at detecting explicitly malicious prompts and assessing toxic content, providing an essential layer of security for LLM applications.</p>
+It excels at detecting explicitly malicious prompts, providing an essential layer of security for LLM applications.</p>
 <p>By embedding Arch-Guard within the Arch architecture, we empower developers to build robust, LLM-powered applications while prioritizing security and safety. With Arch-Guard, you can navigate the complexities of prompt management with confidence, knowing you have a reliable defense against malicious input.</p>
 </section>
 <section id="example-configuration">