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st1nger :unverified: 🏴‍☠️ :linux: :freebsd:<p>Researchers have uncovered a new supply chain attack called <a href="https://infosec.exchange/tags/Slopsquatting" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Slopsquatting</span></a> where threat actors exploit hallucinated, non-existent package names generated by <a href="https://infosec.exchange/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> coding tools like <a href="https://infosec.exchange/tags/GPT4" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>GPT4</span></a> and <a href="https://infosec.exchange/tags/CodeLlama" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>CodeLlama</span></a> </p><p>These believable yet fake packages (amounting to 19.7% or 205,000 packages), recommended in test samples were found to be fakes., can be registered by attackers to distribute malicious code. </p><p>Open-source models -- like <a href="https://infosec.exchange/tags/DeepSeek" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepSeek</span></a> and <a href="https://infosec.exchange/tags/WizardCoder" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>WizardCoder</span></a> -- hallucinated more frequently, at 21.7% on average, compared to the commercial ones (5.2%) like GPT 4. </p><p>We Have a Package for You! A Comprehensive Analysis of Package Hallucinations<br>by Code Generating LLMs (PDF) <a href="https://arxiv.org/pdf/2406.10279" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="">arxiv.org/pdf/2406.10279</span><span class="invisible"></span></a></p>
WetHat💦<p><a href="https://fosstodon.org/tags/Ollama" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Ollama</span></a> models:<br>➡️ <a href="https://fosstodon.org/tags/CodeLlama" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>CodeLlama</span></a> offers versatile development assistance with advanced pattern recognition and infilling capabilities.<br>➡️ Qwen 2.5 Coder transforms debugging by providing intelligent solutions to root causes.<br>➡️ WizardLM2 excels in rapid prototyping and multilingual development.<br>➡️ Mistral 7B is a lightweight model that delivers impressive performance with efficient architecture.</p><p><a href="https://insights.codegpt.co/best-ollama-model-for-coding?form=MG0AV3" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">insights.codegpt.co/best-ollam</span><span class="invisible">a-model-for-coding?form=MG0AV3</span></a></p><p><a href="https://fosstodon.org/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> <a href="https://fosstodon.org/tags/SoftwareDevelopment" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>SoftwareDevelopment</span></a> <a href="https://fosstodon.org/tags/CodeLlama" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>CodeLlama</span></a> <a href="https://fosstodon.org/tags/QwenCoder" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>QwenCoder</span></a> <a href="https://fosstodon.org/tags/WizardLM2" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>WizardLM2</span></a> <a href="https://fosstodon.org/tags/Mistral7B" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Mistral7B</span></a> <a href="https://fosstodon.org/tags/Programming" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Programming</span></a></p>
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