A new fast pointer nullification defense against UAF, resolving decompilation distortions with FidelityGPT, FirmAgent applying fuzzing to assist LLM vulnerability discovery, and FirmCross analyzing C-Lua hybrid firmware.
LLM assistance in reverse engineering, side-channel device tracking in exclusive-use IoT, and defensive measures for differentially private streams and iteratively pruned deep neural networks.
New findings covering auto-contextualized mobile logic bombs, blurred capability boundaries in LLM applications, side-channel attacks on serverless cloud functions, cross-compilation binary alignment, and function name inference in stripped binaries.
Background Autonomous malware analysis requires moving beyond static, predefined containment environments. Modern malware actively fingerprints its execution context, checking CPUID leaves, measuring execution time with RDTSC, and probing for virtualization-specific hardware devices [6, 13]. Traditional sandboxing methodologies rely on a one-size-fits-all containerization approach, which typically embeds an agent inside the guest OS to monitor API calls and system behavior [1, 12]. This in-guest presence provides a highly visible artifact for evasive malware to detect and subvert. ...