Berkeley AI Research Proposes StruQ and SecAlign to Defend Against Prompt Injection

Jul 11, 2026

Berkeley AI Research has introduced two fine-tuning defenses, StruQ and SecAlign, to protect LLM-integrated applications from prompt injection attacks. StruQ and SecAlign reduce the success rates of optimization-free attacks to around 0%, while SecAlign lowers optimization-based attack success rates to below 15%, representing a fourfold improvement over previous state-of-the-art methods across five tested LLMs.

Why it matters: Prompt injection is a leading threat to LLM-integrated applications, and these defenses provide effective, utility-preserving protection without extra computational or human cost.

Full story at: Berkeley AI Research ↗