API Security Risks: How to Detect and Defend with AI

What Is API Security?

API Security is the practice of protecting the application programming interfaces (APIs) that power cloud-first enterprises

Some sources claim that the average organization has 613 APIs* connected to their systems - each a potential security risk to your software supply chain. Sharing data across an API fundamentally means punching a hole in the firewall to ensure bidirectional connectivity. If that API has a vulnerability, cybercriminals could exploit it to gain access to your critical data.

For this reason, understanding the potential risks in the APIs used in your software is absolutely vital for long-term security. Moreover, a surge in AI-driven vulnerabilities creates additional risk for your organization*.

Case in point: In January 2023, T-Mobile* suffered an intrusion via API by threat actors, who used the connection to access and compromise the records of 37 million people. This risk of a data breach via API is very real and could cause substantial issues.

Ultimately, it's because of the risk to the software supply chain and the rise in AI-driven weaknesses that organizations must pay closer attention to weaknesses in APIs.

Why API Security Risks Are Rising in Cloud Production

• API sprawl: Enterprises run hundreds of APIs across microservices and cloud platforms, with little centralized oversight.
• Blind trust in cloud providers: Many assume cloud infrastructure is secure by default, overlooking shared-responsibility gaps.
• Third-party dependencies: External APIs and open-source components introduce risks beyond direct enterprise control.
• Data-rich targets: APIs often provide direct access to sensitive customer, financial, or operational data.

According to Gartner, by 2025, APIs will be the most-frequent attack vector leading to data breaches in enterprise web applications.

Understanding API Vulnerabilities

API vulnerabilities may take many forms, most resulting in remote code execution or privilege escalation.

The Open Worldwide Application Security Project (OWASP)* defined a list known as the Top 10 that outlines the 10 most common application vulnerabilities.

These include:

1. Broken object-level authorization: APIs tend to expose object identifier endpoints. When they do this, it means there's a potential attack surface full of object-level access control issues, which need object-level authorization checks in every function to resolve. These checks should include a function that accesses a data source using identification from the user.
2. Broken authentication: Attackers can exploit an authentication mechanism that wasn't implemented correctly. Many threat actors can make substantial use of broken authentication.
3. Broken object-property-level authorization: This category unifies two older security risks – API3:2019 Excessive Data Exposure and API6:2019 – Mass Assignment. The new standard emphasizes the root cause: lack of or improper authorization validation at the object property level.
4. Unrestricted resource consumption: Satisfying API requests requires resources like network bandwidth, CPU, memory, and storage. Resources like emails, SMS, phone calls, and biometrics are available by service providers via integrations and paid for per request. Overloading the API with requests can lead to denial of service or higher operational costs.
5. Broken function-level authorization: Complex policies for access control with multiple hierarchies, groups, and roles with an unclear distinction between administrative and regular functions tend to lead to authorization flaws. When attackers exploit these issues, they can access other users’ resources and/or administrative functions.
6. Unrestricted access to sensitive business flows: This risk refers to APIs that expose a business flow, like buying a ticket without compensating for how the functionality could harm the business if automated and used excessively.
7. Server-side request forgery (SSRF): Server-side request forgery (SSRF) flaws can happen when an API retrieves a remote resource without validating the user-supplied URI. This enables attackers to trick the application into sending a crafted request to an unexpected destination, regardless of whether it’s protected by a VPN or firewall.
8. Security misconfiguration: APIs and the systems supporting them typically contain complex configurations meant to make the APIs more customizable. Software and DevOps engineers can easily miss these configurations or not follow security best practices when it comes to configuration, which opens the door to attacks.
9. Improper inventory management: APIs often expose more endpoints than traditional web applications, making proper documentation vital. An updated inventory of hosts and deployed API versions is also critical to mitigate issues such as deprecated API versions and exposed debug endpoints.
10. Unsafe consumption of APIs: Developers will often trust data received from third-party APIs more than user input and so tend to adopt weaker security standards. Attackers may go after integrated third-party services instead of trying to compromise the target API directly.

When working in cloud environments, organizations must protect themselves against these common API weaknesses so sensitive information stays secure, and data remains uncompromised. Resolving these weaknesses also limits the likelihood of threat actors gaining a foothold in the organization.

To do this, security teams need solutions that can analyze APIs at scale for any possible weaknesses. This analysis should extend to APIs developed in-house as well as those the organization receives from vendors to connect acquired software.

Supply Chain Risks Hidden in APIs

The modern software supply chain depends on open-source packages, third-party APIs, and managed services. This interconnectedness creates cascade risks:

• A single vulnerable dependency can expose multiple services.
• Malicious code in open-source libraries can propagate across environments.
• External APIs may not meet enterprise security baselines.

The SolarWinds and Log4j incidents underscored how supply chain risks bypass traditional perimeter defenses. APIs amplify this challenge because they operate in dynamic, interconnected ecosystems.

AI and LLMs: A New Approach to Detecting API Security Risks

Conventional tools often fail to keep pace with API complexity. AI and large language models (LLMs) are reshaping production security by:

• Automated detection: AI can scan thousands of APIs and dependencies for misconfigurations, anomalies, and hidden vulnerabilities.
• Pattern recognition: LLMs analyze attack flows across multi-stage intrusions that traditional rule-based systems miss.
• Adaptive defense: AI models learn from new exploits, enabling faster updates and proactive defenses.
• Supply chain mapping: Intelligent correlation of open-source components and third-party APIs helps detect hidden backdoors.

This data-driven approach extends beyond APIs, providing a unified view of production security risks.

From APIs to Production Security: Building a Resilient Framework

Securing APIs is not a standalone task. CISOs must embed it into a holistic production security strategy that unites people, process, and technology:

• People: Upskill DevSecOps teams on API-first threat modeling.
• Process: Integrate API security testing into CI/CD pipelines.
• Technology: Use AI-driven detection, continuous monitoring, and contextual risk scoring.

This unified approach reduces alert fatigue, prioritizes business impact, and aligns SecOps with enterprise resilience goals.

The Role of AI-Powered MDR in API Security

Most enterprise internet traffic today originates from APIs making continuous calls to their sources. This dependency makes APIs a prime attack surface for organizations that don’t rigorously monitor behavior in production environments.

AI tools help close this gap by:

• Monitoring API endpoints in real time for anomalies such as unexpected connections, unusual payloads, or abnormal traffic spikes.
• Correlating API activity with network telemetry to detect hidden attack patterns.
• Prioritizing signals with business context, ensuring SOC teams focus only on the most critical threats.

This is where AI-powered managed detection and response (MDR) solutions, such as those from Netenrich, extend value. They combine continuous monitoring, automated triage, and contextual enrichment to:

• Surface only the most severe API errors for human intervention.
• Automate responses to low-level anomalies, reducing analyst fatigue.
• Provide SOC teams with the intelligence needed to defend critical systems at speed.

By augmenting human teams with AI-powered MDR, CISOs can reduce operational drag, strengthen API defense, and prevent blind spots across cloud production environments.

Modern Defense Starts Where API Blind Spots End

APIs are the connective tissue of today’s digital supply chain. Left unsecured, they become invisible entry points for attackers.

Embedding AI-driven monitoring and MDR capabilities into production security strategies ensures:

• Faster detection of anomalous API activity.
• Automated defenses against commodity threats.
• Efficient allocation of analyst time toward the highest-risk incidents.

Ultimately, AI-powered SecOps provides the speed, context, and automation needed to match the complexity of cloud-native operations. For CISOs, this means moving beyond the assumption that “cloud is safe by default” and proactively engineering resilience into every API-driven process.

FAQs

1.What are API security risks in cloud production?

API security risks are vulnerabilities like broken authentication, data exposure, and unvalidated dependencies that attackers exploit in cloud environments.

2.Why are API vulnerabilities overlooked by enterprises?

Most enterprises assume cloud platforms provide complete security, ignoring the shared responsibility model and hidden risks in APIs.

3.How do third-party APIs increase security risks?

Third-party APIs may contain vulnerabilities, weak controls, or malicious code that expose enterprise applications and data.

4.How can AI help reduce API security risks?

AI and LLMs detect misconfigurations, analyze attack flows, and uncover vulnerabilities at scale that traditional tools miss.

5.What’s the link between API security and production security?

APIs are integral to production systems; securing them is a critical pillar of overall production security.

*Sources:

• The hacker news | API’s Drive Majority of the Traffic
• Cybersecurity Dive | Experts question T-Mobile’s security culture as breach cycle churns
• Infosecurity magazine | AI Surge Drives Record 1205% Increase in API Vulnerabilities
• OWASP.org | OWASP API Security Top 10