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This work formalizes poison selection as oracle-budgeted set optimization and introduces SAILS (Set-level Audit-Informed Iterative Learned Selection), which learns a set scorer from a few hundred finetune-and-evaluate runs, ranks millions of candidate sets, and audits only a small shortlist.
P RO A CT represents an orthogonal defense strategy that serves as an additional guardrail to enhance LLM safety against the most effective attacks.
This paper introduces CryptanalysisBench, 191 tasks across six families of cryptographic primitives drawn primarily from four NIST standardization competitions, and releases CryptanalysisBench as a tool to help track if (or when) AI cryptanalysis becomes a serious factor and as a scaffold for stress-testing candidate s...
This paper presents Untrusted Content Masking (UCM), a simple and effective approach that restores the trust boundary in web environments by leveraging a key structural insight: a webpage's Document Object Model encodes sufficient information to distinguish trusted from untrusted regions without reading their content.
SRE-Bench is introduced, the first realistic, contamination-free RE benchmark, and results indicate that strong source-code security capabilities do not yet transfer to binary analysis, highlighting RE as an important frontier for agentic cybersecurity and SRE-Bench as a rigorous testbed to measure progress.
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