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MoLIFE redefines mobile forensics by enabling secure data acquisition without compromising evidence integrity, even in the face of stringent data protection measures.
Existing problem-space attacks are largely impractical, but DROIDBREAKER shows how to craft adversarial APKs that evade detection while preserving functionality.
"Clean" SAST reports on obfuscated JavaScript code are often a mirage, as even basic obfuscation techniques can blind state-of-the-art tools to critical vulnerabilities.
Slash malware detection labeling costs by 90% using combined active and semi-supervised learning, without sacrificing performance.
LLMs can now automate and explain memory forensics, extracting more malware indicators of compromise than existing tools and making analysis accessible to non-experts.
