Revelio combines LLMs, static analysis, and sanitizer-verified PoVs to scalably discover memory safety vulnerabilities in repository-scale code, finding 19 new bugs in long-fuzzed projects at low cost.
One bug, hundreds behind: Llms for large-scale bug discovery,
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3representative citing papers
Non-model gains via inference, systems, and assets can drive AI capabilities independently of base models, requiring governance beyond model-level evaluation and mitigation.
AnyPoC validates LLM bug reports by synthesizing, executing, and independently re-checking proof-of-concept tests, finding 121 new bugs with 108 confirmed across large systems.
citing papers explorer
-
Revelio: Cost-Efficient Agentic Memory Safety Vulnerability Detection For Repository-Scale Codebases
Revelio combines LLMs, static analysis, and sanitizer-verified PoVs to scalably discover memory safety vulnerabilities in repository-scale code, finding 19 new bugs in long-fuzzed projects at low cost.
-
Comprehensive AI governance requires addressing non-model gains
Non-model gains via inference, systems, and assets can drive AI capabilities independently of base models, requiring governance beyond model-level evaluation and mitigation.
-
AnyPoC: Universal Proof-of-Concept Test Generation for Scalable LLM-Based Bug Detection
AnyPoC validates LLM bug reports by synthesizing, executing, and independently re-checking proof-of-concept tests, finding 121 new bugs with 108 confirmed across large systems.