Recent research highlights a critical shift in cybersecurity as AI evolves from passive chat interfaces into autonomous agentic systems capable of executing complex financial and digital actions. These sources document the discovery of end-to-end exploit chains, such as indirect prompt injections targeting the Model Context Protocol (MCP), which allow attackers to hijack a model’s reasoning to perform unauthorized transactions. To combat these emerging threats, new automated frameworks like RedCodeAgent and BlueCodeAgent have been developed to systematically discover and defend against vulnerabilities in AI-generated code and tool-calling procedures. Specialized security tools, including VirtueGuard, are also introduced to provide real-time, privacy-focused monitoring within enterprise environments. Ultimately, the industry is urged to adopt intent-aware guardrails and rigorous sandboxing to ensure that the productivity gains of autonomous AI do not come at the cost of catastrophic systemic risk.