Microsoft Builds Scanner to Detect Backdoors in LLMs
🔍 Microsoft has developed a lightweight scanner to detect backdoors in open-weight large language models (LLMs) by evaluating three observable signals tied to internal model behavior. The tool extracts memorized content, isolates suspect substrings, and scores candidates with loss functions that formalize attention and output anomalies. The approach requires no additional training and runs across common GPT‑style models, but it needs access to model files and is best suited for trigger-based, deterministic backdoors.
