Security at AI Speed: You Can’t Fix What You Can’t Detect and Understand

The rise of AI in coding is significantly impacting software security, with AI-generated code often containing vulnerabilities and being exploited faster than ever before. According to New Relic's 2026 report, a substantial portion of weekly code is either AI-generated or refactored by AI, with many teams releasing it without thorough verification. Veracode's testing reveals that AI models frequently introduce security vulnerabilities, while frontier AI models like Anthropic's Mythos are rapidly identifying software bugs, aiding attackers in quick exploitation. The timeline from a bug's disclosure to its exploitation has drastically shortened, highlighting the urgent need for enhanced code security. Emerging threats, such as Agentjacking, evade traditional security tools, which struggle to detect new and complex risks posed by AI-generated code. The necessity for security tools to adopt an agentic approach—mirroring the reasoning of a senior engineer—becomes evident, as they must detect and explain vulnerabilities clearly to developers for effective remediation. As AI accelerates coding and introduces novel risks, the industry must adapt its security reviews to keep pace with these changes, emphasizing the importance of reasoning and explainability in addressing high-signal security vulnerabilities.

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