This paper investigates the security vulnerabilities in SNARKs (Succinct Non-Interactive Arguments of Knowledge), focusing on the end-to-end security properties of real-world implementations. SNARKs are non-interactive protocols that allow a prover to generate a succinct proof of a computational statement, which can be efficiently verified by a verifier. Despite their theoretical security, practical implementations of SNARKs have revealed numerous vulnerabilities. The paper provides a comprehensive analysis of 141 vulnerabilities in SNARK implementations, offering a detailed taxonomy to help developers and researchers understand the security threats in SNARK-based systems. It also evaluates existing defense mechanisms and offers recommendations for improving the security of SNARK-based systems. The paper introduces a four-layer system model for SNARKs, including the Circuit Layer, Frontend Layer, Backend Layer, and Integration Layer. Each layer presents unique challenges and vulnerabilities. In the Circuit Layer, vulnerabilities often arise from incorrect constraints or under-constrained circuits, leading to issues with soundness, completeness, and zero-knowledge. In the Frontend Layer, vulnerabilities can occur during the compilation of high-level code to a SNARK-friendly representation. In the Backend Layer, vulnerabilities may involve the prover or verifier components, such as misconfigurations or flaws in the proof system. In the Integration Layer, vulnerabilities can result from improper interactions between the application and the SNARK components, or from design flaws that compromise the system's security. The paper also introduces a taxonomy of adversarial roles and the impact of vulnerabilities on SNARK systems. Adversaries can include network adversaries, adversarial users, and adversarial provers, each with different levels of knowledge and potential impact. The paper categorizes vulnerabilities based on their impact, including breaking soundness, completeness, and zero-knowledge. It also discusses the root causes of these vulnerabilities, such as incorrect translations of logic into constraints, missing input constraints, and unsafe reuse of circuits. The paper concludes with recommendations for improving the security of SNARK-based systems, including adding missing constraints, improving documentation, and using specialized security tools. It emphasizes the importance of rigorous testing and validation of SNARK implementations to ensure their security and reliability. The study highlights that SNARKs are not just "math" but complex systems where cross-layer interactions can introduce vulnerabilities, and that a holistic approach is needed to ensure their security.This paper investigates the security vulnerabilities in SNARKs (Succinct Non-Interactive Arguments of Knowledge), focusing on the end-to-end security properties of real-world implementations. SNARKs are non-interactive protocols that allow a prover to generate a succinct proof of a computational statement, which can be efficiently verified by a verifier. Despite their theoretical security, practical implementations of SNARKs have revealed numerous vulnerabilities. The paper provides a comprehensive analysis of 141 vulnerabilities in SNARK implementations, offering a detailed taxonomy to help developers and researchers understand the security threats in SNARK-based systems. It also evaluates existing defense mechanisms and offers recommendations for improving the security of SNARK-based systems. The paper introduces a four-layer system model for SNARKs, including the Circuit Layer, Frontend Layer, Backend Layer, and Integration Layer. Each layer presents unique challenges and vulnerabilities. In the Circuit Layer, vulnerabilities often arise from incorrect constraints or under-constrained circuits, leading to issues with soundness, completeness, and zero-knowledge. In the Frontend Layer, vulnerabilities can occur during the compilation of high-level code to a SNARK-friendly representation. In the Backend Layer, vulnerabilities may involve the prover or verifier components, such as misconfigurations or flaws in the proof system. In the Integration Layer, vulnerabilities can result from improper interactions between the application and the SNARK components, or from design flaws that compromise the system's security. The paper also introduces a taxonomy of adversarial roles and the impact of vulnerabilities on SNARK systems. Adversaries can include network adversaries, adversarial users, and adversarial provers, each with different levels of knowledge and potential impact. The paper categorizes vulnerabilities based on their impact, including breaking soundness, completeness, and zero-knowledge. It also discusses the root causes of these vulnerabilities, such as incorrect translations of logic into constraints, missing input constraints, and unsafe reuse of circuits. The paper concludes with recommendations for improving the security of SNARK-based systems, including adding missing constraints, improving documentation, and using specialized security tools. It emphasizes the importance of rigorous testing and validation of SNARK implementations to ensure their security and reliability. The study highlights that SNARKs are not just "math" but complex systems where cross-layer interactions can introduce vulnerabilities, and that a holistic approach is needed to ensure their security.