A specialized artificial intelligence security auditor developed by ZKSecurity has identified and helped resolve a critical soundness vulnerability in OpenVM, an open-source zero-knowledge virtual machine. The flaw, tracked as CVE-2026-46669, resided in the openvm-pairing guest library and allowed malicious provers to forge pairing equality checks, potentially compromising any decentralized application, cross-chain bridge, or privacy protocol relying on the vulnerable component. OpenVM maintainers promptly addressed the issue in version 1.6.0, and partner projects have since completed upgrades. The vulnerability stemmed from an optimization technique designed to replace computationally expensive final exponentiation with a cheaper algebraic verification. This method requires a scaling factor to remain within a specific mathematical subfield. However, OpenVM implementation only verified that the prover-supplied hint was non-zero, omitting the essential subfield membership check. Without this constraint, attackers could substitute arbitrary values to satisfy the verification equation, effectively bypassing cryptographic soundness guarantees. The remediation reintroduced the missing validation, ensuring scaling factors conform to the required subfield constraints. This discovery highlights the evolving role of artificial intelligence in cryptographic verification. Initial audits using standard large language models failed to detect exploitable flaws in OpenVM densely interconnected codebase, confirming that isolated, module-level analysis is insufficient for complex zero-knowledge systems. The ZKSecurity team proprietary auditor, zkao, which encodes expert cryptographic triage workflows, successfully navigated the framework architectural complexity after over nine hours of scanning. The team noted that automated proof-of-concept generation remains unreliable for vulnerability triage, as models frequently produce syntactically valid but logically flawed exploit scripts. Human-in-the-loop validation remains critical for distinguishing genuine security defects from false positives. Following the resolution, OpenVM and ZKSecurity initiated a targeted security assessment for the upcoming 2.0 release. The findings underscore the necessity of specialized AI auditing pipelines tailored to cryptographic codebases, where modular isolation techniques fall short and deep contextual analysis is required. Organizations operating zero-knowledge proof systems are advised to ensure they are running OpenVM 1.6.0 or later. The development team plans to publish subsequent analyses detailing additional findings from the next-generation release.