Our principal shares critical insights on the accumulation of security debt in today's AI implementations. Just as we battled legacy security issues from the early web era, hastily deployed AI systems are creating tomorrow's security vulnerabilities. This post explores how non-deterministic behavior, complex interdependencies, and surface-level understanding create unique security challenges for organizations adopting AI. This analysis informs how we approach security assessments for AI systems, focusing on both immediate vulnerabilities and long-term security architecture. #AISecurityDebt #SecurityAssessment #AIRisk
Helping Organizations Secure Web, Mobile, API & AI Applications | 15+ Yrs Pen Testing | Principal @ Appsurent | 🇨🇦
The next post on my series of in-the-trenches AI security lessons learned: 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗗𝗲𝗯𝘁: 𝗛𝗼𝘄 𝗧𝗼𝗱𝗮𝘆'𝘀 𝗔𝗜 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻𝘀 𝗪𝗶𝗹𝗹 𝗛𝗮𝘂𝗻𝘁 𝗨𝘀 𝗧𝗼𝗺𝗼𝗿𝗿𝗼𝘄 As I test more and more AI systems and applications generated in whole or in part by GenAI. It's clear we're building tomorrow's security debt today with rushed deployments and vibe-coded applications. 2000: "Just get the website up!" - "We'll fix the security issues later." 2025: "Just get the AI working!”- "We'll add guardrails once it's in production." The AI tools and AI generated applications rushed into production now, may soon become the legacy headaches for four key reasons: • 𝗡𝗼𝗻-𝗱𝗲𝘁𝗲𝗿𝗺𝗶𝗻𝗶𝘀𝘁𝗶𝗰 𝗯𝗲𝗵𝗮𝘃𝗶𝗼𝘂𝗿 of GenAI systems makes vulnerabilities harder to consistently detect and verify • 𝗔𝗴𝗲𝗻𝘁, 𝗠𝗼𝗱𝗲𝗹 𝗮𝗻𝗱 𝗧𝗼𝗼𝗹 𝗶𝗻𝘁𝗲𝗿𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝗰𝗶𝗲𝘀 create complex attack surfaces that are poorly documented and only just being understood. • 𝗦𝘂𝗿𝗳𝗮𝗰𝗲 𝗟𝗲𝘃𝗲𝗹 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 provides perfect hiding places for vulnerabilities • 𝗘𝘃𝗼𝗹𝘃𝗶𝗻𝗴 𝗮𝘁𝘁𝗮𝗰𝗸 𝘁𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀 will expose flaws in today's "secure enough" implementations Simply relying on prompt-based guardrails ("don't do X") is the equivalent of escaping double quotes in queries and calling it a day. By 2026, expect more AI-specific CVEs, major remediation projects, and complete system rebuilds when security debt becomes unmanageable. The most dangerous assumption? That AI systems are too novel for traditional security principles to apply. They actually require both traditional and new AI-specific controls. So please make sure to perform a security assessment of the code generated by AI and please don't give the new shiny AI Agent a service account with domain administrator privileges. #AISecurity #TechnicalDebt #SecurityLeadership
