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                     <h4>⚠️ Honest Assessment: The Goal is Economic Disruption, Not Perfect Unbreakability</h4>
-                    <p>Recent research (LightShed, USENIX 2025) demonstrated autoencoder-based attacks that can learn to remove protection patterns when trained on large, paired clean/armored image datasets. <strong>When an attacker has access to both original and protected versions of many images, Poisonous Shield for Images can be removed.</strong></p>
+                    <p>Recent research (LightShed, USENIX 2025) demonstrated autoencoder-based attacks that can learn to remove protection patterns when trained on large, paired clean/armored image datasets. <strong>When an attacker has access to both original and protected versions of many images, protection algorithms like Nightshade, Glaze, Metacheck, Poisonous Shield for Images, etc can be removed. No current solution exists that is able to overcome this autoencoder approach unfortunately.</strong></p>
                     <p style="margin-top: 12px;"><strong>The Economic Hurdle Strategy:</strong> The primary goal of Poisonous Shield for Images is to make unauthorized AI training prohibitively expensive and time-consuming. We achieve this in two ways:</p>
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                         <li><strong>Cost of Removal:</strong> To train a removal model, attackers must acquire thousands of paired (clean, protected) images. This forces them to either license/purchase original content from creators or use our service to generate armored versions—both creating significant financial and logistical barriers.</li>