As organizations race to integrate agentic AI into their development and operations workflows, a critical pattern is emerging. AI autonomy is outpacing security maturity. While agentic systems promise productivity and speed, they also introduce entirely new pathways for misuse and exploitation.
But here’s the real story: agentic AI isn’t just “new.” It mirrors an old challenge in a more dangerous form.
Much of the risk we face with autonomous agents resembles the same risks we’ve wrestled with in API security for a decade, except now they’re amplified, accelerated, and easier to exploit. And the connective tissue between the two is the rise of non-human identities (NHIs).
Understanding these similarities will help organizations stay ahead by applying proven software security principles and investing early in the upskilling required for responsible and defensive AI adoption.
If you are considering incorporating AI agents into your workflows or have already done so, now is the time to take stock. Below are the key risks you should understand, along with practical steps (including training) to mitigate them.
The Core Problem: AI Agents Are Non-Human Identities with Expanding Privileges
Agentic AI systems act, decide, and execute on behalf of an organization, requiring credentials, access, and the ability to utilize tools and APIs. In other words, they become non-human identities, equivalent to:
- Service accounts
- Machine users
- Scripted automation
- API clients
- CI/CD runners
The difference is that AI agents behave unpredictably, interact with untrusted content, and can be manipulated through language, not code.
In their article The Attack Surface: How Agents Raise the Cyber Stakes, Dark Reading characterized autonomous agents as “digital insiders” capable of taking actions traditionally reserved for privileged human users. If compromised, misconfigured, or manipulated, they can impact systems with a speed and scale that far exceeds manual access.
Identity-centric security has long been considered best practice for APIs and automation, and it now applies directly and urgently to AI.
APIs and Agentic AI: More Similar Than You Think
APIs opened a new era of machine-to-machine interaction. Agentic AI is extending that into machine-to-resource and machine-to-action autonomy. But fundamentally, they share three characteristics:
1. Both expose structured capabilities that attackers can exploit
APIs expose functions; AI agents expose tools and workflow logic. If the input isn’t validated or the behavior isn’t constrained, both become dangerous.
2. Both rely on credentials and permissions
API keys, OAuth tokens, and service identities introduced identity-sprawl long before AI arrived. Agentic AI amplifies it: each agent needs its own identity, isolation, and least-privilege model.
3. Both are only secure when guardrails and boundaries are explicit
For APIs, this means rate limiting, schema validation, and strict access control. For agents, it means scoped prompts, safe tool invocation, and sandboxed execution.
The key difference?
- APIs follow deterministic logic.
- AI agents follow statistical reasoning, making them vulnerable to manipulation via language, context, or environmental cues.
This is why the security principles that protect APIs also form the foundation of responsible AI deployment. They just need to be expanded to accommodate new attack modes like prompt injection and goal hijacking.
Foundational Software Security Principles Apply Now More Than Ever
Agentic AI doesn’t replace software security fundamentals. It stress-tests them.
Below are the timeless principles that must be applied directly to AI systems:
| Least Privilege |
- Grant agents the minimum capabilities required.
- Do not reuse human credentials.
- Enforce role-based access for NHIs just as aggressively as for APIs. |
| Separation of Duties |
- Don’t let a single agent handle sensitive, end-to-end workflows.
- Break tasks into segmented responsibilities — especially those involving data, authentication, or deployment. |
| Input Validation & Output Control |
- Prompt injection demonstrates that “input validation” now includes language, context, and content ingestion.
- Every output should be checked before execution, just as you would validate API responses before using them downstream. |
| Identity Isolation & Credential Hygiene |
Agents require durable identities — API-like service accounts — with short-lived tokens, rotation policies, and full auditability. |
| Secure Defaults |
Just as API gateways block risky calls by default, AI orchestrators must block unapproved tool use, untrusted code execution, and high-risk actions without human approval. |
| Defense in Depth |
- Combine sandboxing, logging, observability, and approval workflows.
- AI autonomy demands layered controls, not single gates. |
These principles protected us through cloud adoption and API proliferation. If applied rigorously and intentionally, they will protect us through the AI era.
Why AI Literacy Is Now a Core Security Skill
AI literacy has surpassed traditional programming as the most critical skill for developers. That’s because agentic AI:
- rewrites workflows
- shifts the boundary between trusted and untrusted inputs
- requires a new understanding of threat modeling
- blends software behavior with human-like reasoning
Teams without AI literacy face the risk of deploying agents that:
- overreach their permissions
- mis-handle sensitive data
- escalate privileges unintentionally
- execute malicious instructions
- generate vulnerable code
AI literacy is more than just knowing how to use AI. It’s about understanding how AI interacts with your system securely.
CMD+CTRL Helps Teams Deploy AI Responsibly and Defend Against AI-Driven Risks
CMD+CTRL’s training programs provide teams with the knowledge, hands-on practice, and defensive coding skills necessary to safely deploy AI and APIs while managing the surge of non-human identities that accompanies agentic systems.
Our courses and cyber ranges help teams:
- Master AI-Aware Software Security
- Apply Secure Development Practices to AI Workflows
- Manage Non-Human Identities Like First-Class Citizens
- Elevate API Security Skills — Foundational for Agentic AI
- Train Through Realistic, Hands-On Scenarios
The Next Era of AppSec Depends on How We Secure Non-Human Identities
By viewing AI agents as non-human identities, applying API security discipline, and reinforcing foundational software security principles, organizations can harness AI’s power without inheriting unnecessary risk. But that requires a workforce trained in modern AppSec, AI literacy, and defensive coding.
CMD+CTRL delivers hands-on, up-to-date training and realistic labs to help teams secure AI-enabled systems. Check out our courses and labs on APIs and AI to prepare your teams to deploy AI securely. Contact us today to learn more.