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DarKnight, a self-improving agentic framework designed to run on a single workstation GPU inside an investigator's Tor crawler and solve CAPTCHAs with small, locally hosted open-weight VLMs that no provider decision can withdraw, without per-market training or third-party services is presented.
Effective source recovery is critical to security applications such as malware analysis, vulnerability assessment, and legacy maintenance. Large Language Models (LLMs) are reshaping this field, shifting the paradigm away from rule-based heuristics to probabilistic and high fidelity semantic recovery of source code from...
Toketive is introduced, a simple yet powerful reference-free attack that exploits the tokenization-based side channel to detect modified knowledge and reconstruct the corresponding pre-edit response and shows that localized modifications should not be treated as robust knowledge-control boundaries without adversarial e...
Candidate generation for open-source vulnerabilities is no longer scarce. AI-assisted code review now produces defect candidates cheaply, and industry programs pair them with expert human triage. The remaining scarcity is validation and impact assessment, and the gap is largest in critical-infrastructure software like...
This work presents CHISEL, a test suite-free framework to iteratively recover source code from Ghidra-derived pseudo-C, and systematically evaluates CHISEL for compilation and semantic recovery, feedback oracle soundness, and iteration overhead on 120 ExeBench functions compiled for the x86-64 architecture.
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