When APIs become the enterprise backdoor -- securing AI’s most vulnerable link [Q&A]

APIs were once treated as behind-the-scenes connectors. Today, they are the enterprise nervous system, linking cloud workloads, data platforms, SaaS tools, and increasingly, autonomous AI agents. This centrality makes them irresistible targets.

According to multiple industry reports, API-related vulnerabilities are among the fastest-growing classes of security incidents. The problem isn’t just exposure; it’s amplification. A single unprotected API can open the door to everything it touches, from sensitive customer records to critical operational systems.

We spoke with Scott Wheeler, cloud practice lead at Asperitas, to discover why API risk is no longer just an IT issue; it’s a board-level business continuity issue.

BN: How do agentic AI systems change the API security landscape?

SW: Agentic AI doesn’t just use APIs, it lives through them. Autonomous agents call APIs to fetch data, execute processes, and even make procurement or operational decisions without direct oversight. That autonomy raises the stakes. If those API interactions are compromised, attackers could feed false data to models, reroute workflows, or subtly shift outputs in ways that are almost impossible to detect until damage is done. Unlike a human operator, an AI agent doesn’t 'sense' something is off. It will trust the API response and act accordingly. That blind trust is both the strength and the Achilles’ heel of agentic AI.

BN: What’s wrong with traditional perimeter-based security models in this new environment?

SW: Perimeter models assume you can build a wall around trusted systems and monitor ingress points. But in a world of distributed architectures, hybrid clouds, and AI agents making calls across multiple domains, there is no fixed ‘inside’ anymore. Every API endpoint is a new border crossing. Once an attacker finds a way past one weak link, they can often pivot laterally without resistance. The implication is clear: organizations must abandon the mindset of a single ‘fortress’ perimeter and instead enforce continuous, contextual validation for every interaction, no matter where it originates.

BN: What does an ‘API-first security strategy’ look like in practice?

SW: An API-first strategy begins with a fundamental shift in mindset: APIs are not just developer conveniences, they are business-critical assets that demand the same rigor as financial systems or customer databases. In practice, this means organizations must elevate APIs to the center of their security architecture rather than treating them as afterthoughts. Every API should be discoverable, monitored in real time, and evaluated against patterns of expected behavior. Security should be integrated from design through deployment, with contextual access controls that adjust dynamically based on risk signals. When enterprises adopt this approach, APIs stop being the weak link and instead become a controlled, auditable layer of trust across the enterprise ecosystem.

BN: How does behavior-based threat detection improve API security?

SW: Signature-based defenses are brittle in a world of adaptive adversaries. Behavior-based systems analyze usage patterns over time: who is calling an API, how often, with what payloads, and in what sequence. An anomalous spike in requests or an unusual data request at 3 a.m. could be the early indicator of credential abuse or data exfiltration. The power here is adaptability: behavior models can detect unknown or ‘zero-day’ attacks that don’t match any known signature, giving defenders a fighting chance to stop threats before they spread.

BN: Why is auditability of API calls so important for AI adoption?

SW: Trust is the currency of automation. When AI systems act autonomously, executives, regulators, and customers all want assurance that decisions are traceable and defensible. Audit logs provide that assurance. With a complete, tamper-proof record of every API call (who made it, what data was exchanged, what system responded, etc.) organizations can reconstruct incidents, prove compliance, and uncover attempted manipulations. Without this, enterprises risk operating ‘black box’ systems with no accountability, a scenario regulators are increasingly unwilling to tolerate.

BN: What types of attacks are most likely if organizations fail to secure their APIs?

SW: The attack vectors range from the obvious to the insidious. Weak authentication can allow attackers to slip through the cracks and gain direct access to sensitive systems, while more subtle techniques involve manipulating the data flowing through APIs to distort the outcomes of AI models or decision-making engines. Third-party integrations create another layer of exposure, where a compromise in a partner’s API ripples across the supply chain. And then there is the slow-drip threat of data exfiltration, where APIs are used as a stealth channel to siphon information over time, often escaping notice until it’s far too late. What makes these attacks particularly dangerous is that they can resemble ordinary traffic patterns, making them difficult to spot without dedicated monitoring and anomaly detection.

BN: What should enterprises prioritize over the next 24 months to get ahead of the threat?

SW: The most important step enterprises can take is to bring visibility and accountability to their sprawling API landscapes. Many organizations are shocked when they discover the sheer number of APIs in use, including ‘shadow’ APIs that were created outside of IT oversight. Once the scope is understood, the priority becomes shifting security left, embedding protection into the design and development lifecycle rather than bolting it on after deployment. Finally, organizations need to treat governance not as a compliance exercise but as a dynamic framework that evolves alongside the business. That means real-time monitoring, contextual access controls, and the ability to rapidly respond to anomalies. Enterprises that build this discipline will be positioned to embrace agentic AI with confidence. Those that delay may find their most strategic digital initiatives undermined by a threat vector they underestimated.

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