Towards Scalable and Interpretable Mobile App Risk Analysis Via Large Language Models

Mobile application marketplaces are responsible for vetting apps to identify and mitigate security risks. Current vetting processes are labor-intensive, relying on manual analysis by security professionals aided by semi-automated tools. To address this inefficiency, we propose Mars, a system that...

Learning from the Good Ones: Risk Profiling-Based Defenses against Evasion Attacks on DNNs

Safety-critical applications such as healthcare and autonomous vehicles use deep neural networks DNN to make predictions and infer decisions. DNNs are susceptible to evasion attacks, where an adversary crafts a malicious data instance to trick the DNN into making wrong decisions at inference time...

Modernizing Your VM Program with Rapid7 Exposure Command: A Path to Effective Continuous Threat Exposure Management

In today’s threat landscape, where cyber-attacks are increasingly sophisticated and pervasive, organizations face the daunting challenge of securing a constantly expanding attack surface. Traditional vulnerability management VM programs, while necessary, are no longer sufficient on their own. The...