- Visibility is the prerequisite for security. Rapidly changing AI environments create visibility gaps that attackers exploit; continuous inventory discovery eliminates this risk by ensuring security teams see every API and agent interaction in real time.
- Shadow AI and MCP servers create unmanaged backdoors. Developers often bypass protocols to ship AI features quickly, but unmonitored connections to sensitive data sources allow prompt injections to trick agents into deleting records or exfiltrating databases.
- Traditional controls cannot keep pace with machine-speed exploitation. AI-assisted development often results in fragile APIs and insecure authorization; a layered runtime protection model is required to defend against attackers that use AI to weaponize flaws in minutes.
- Agent-to-agent interactions expand the attack surface exponentially. As internal agents connect to external tools, a single compromised external agent can feed tainted data back into the corporate network, leading to unauthorized data leaks across the entire chain.
- Security must evolve into a strategic business enabler. Rather than blocking AI innovation, organizations should implement automated AI gateways and guardrails that inspect every prompt and response to ensure applications remain resilient, compliant, and secure.
Key takeaways
Frequently Asked Questions (FAQ)
Frequently Asked Questions (FAQ)
The study found that 87% of organizations experienced an API-related security incident in the past year, which is a significant increase from 76% in 2024.
Vibe coding prioritizes rapid delivery and functional demos over rigorous architecture, which often results in fragile APIs, insecure authorization, and error leakage that provides attackers with a roadmap of internal infrastructure.
Only 18% of organizations feel “well prepared” to handle attacks involving APIs linked to AI.
It automatically discovers and tags GenAI and LLM API endpoints, building a comprehensive inventory based on traffic and code repositories, often finding 30%–40% more endpoints than are documented.
It provides prompt injection defense to neutralize malicious inputs, data redaction to mask sensitive information like PII, and agent/model guardrails to filter out toxic or biased content.
Gartner projects that by the end of 2026, roughly 40% of enterprise applications will embed task-specific AI agents, up from just 5% in the previous year.
In 2024, only 18% of organizations ranked API security as a top priority, but by 2026, 52% of security professionals rated it as their number one ranked risk.