The security paradox of local LLMs
Local LLMs, often chosen for enhanced privacy and security, actually pose greater security risks than cloud-based frontier models due to their weaker reasoning capabilities. Research on gpt-oss-20b revealed that attackers can manipulate local models to inject malicious code with up to 95% success rates by disguising backdoors as harmless "easter eggs" or using cognitive overload techniques. These vulnerabilities...