POLYFLOW: A Neuro-Symbolic Framework for Static Cross-Language Information Flow Analysis
POLYFLOW combines neural and symbolic analysis to track information flows across language boundaries in polyglot codebases—targeting a class of cross-language vulnerabilities that conventional SAST tools routinely miss.
Summary written by editorial AI · Source link below
arXiv:2608.29808v1 Announce Type: new Abstract: Modern software systems are commonly constructed in multiple, interacting programming languages. This construction leads to additional, often stealthy vulnerabilities buried in complex information flow due to language interactions. Existing static analyzers are impeded by the heterogeneous semantics of different languages, whereas dynamic approaches suffer from the limited coverage of (available and/or generated) test inputs. In this paper, we dev
Editorial Analysis
European enterprises increasingly run polyglot microservice stacks; vulnerabilities at language boundaries represent an under-tested attack surface that the EU Cyber Resilience Act will expect vendors to address.
Assess whether your SAST toolchain covers cross-language data flows and pilot neuro-symbolic analysis tools for polyglot applications.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
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