Introduction to Zero Day API Threats
A zero day API threat is when a malicious actor identifies a vulnerability within an API that was previously unknown. As the attacking group is the first party to find this vulnerability, the company being attacked has absolutely no idea where or what the vulnerability is. Without any previous cybersecurity case studies to rely on, zero day API threats force companies to defend themselves while completely blind.
The enormous lack of visibility in zero day API threats is one of the reasons they are so disastrous for businesses. Especially considering how central APIs are to the functioning of modern enterprises, any vulnerability in an API can quickly become a company-wide issue.
The Challenges of Detecting Zero Day Exploits
Detecting a zero day exploit in any capacity is difficult because it’s a unique form of attack. However, it becomes even more difficult considering the large number of APIs that the average company will use. Most enterprises will have 100s of APIs that connect various systems, creating a large attack surface to actively monitor.
Here are some of the main challenges of detecting zero day API exploits:
- High-Traffic Channels: APIs are connective tools that receive a very high number of payloads. Considering the sheer volume of traffic to analyze as it passes through API systems, it can be difficult to distinguish normal peaks in activity from malicious spikes from a cybersecurity threat.
- Unknown Attack Vectors: Zero day exploits have never been encountered before by security teams, meaning there is no information on their signatures or vector styles.
- False Positive Rates: As an extension of the previous two issues, the imprecision of detection and the lack of a clear understanding of the attack vector mean that there are many false positives when it comes to zero day exploits. These can tire out your security team and lead to alert fatigue.
The Role of AI in API Security
Artificial intelligence is a major improvement to API security, as it offers businesses the ability to monitor the entire attack surface and precisely detect irregularities.
Here are the four main roles that AI plays in API security:
- Establishing a Contextual Normal: The most effective method of detecting an API zero day exploit is to identify behavioral anomalies in your system. AI tools can analyze your existing workloads to determine what ‘normal’ looks like for each component in your specific business. From that baseline, it can instantly trigger an alert if one API or component begins to show irregularities, expediting your security response.
- Processing Multiple Telemetry Streams: One of the major advantages of using AI in API security is that it can process various streams of telemetry data concurrently. By understanding how different APIs interact and analyzing their traffic, access logs, activity, and more, AI API security systems can build up a context-rich understanding of potential threats.
- Learning and Improving: Over time, artificial intelligence systems use machine learning to continue to develop their technology and improve. Refining their sensors and understanding of your company’s security context will make these tools even more powerful as they improve. For example, continual training will help to decrease the number of false positives.
Best Practices for AI-Driven API Security
While AI API security is a powerful solution by itself, creating an environment where it can thrive will enhance its efficiency and productivity in your organization.
Here are three of the best practices for using AI in API security:
- Maintain Visibility Over Your APIs: Without full visibility over your APIs and your wider attack surface, it’s impossible to know where threats could originate from. Conduct auditing and use attack surface identification strategies to effectively map out your entire enterprise ecosystem. From there, you’ll be able to ensure that your AI system is effectively monitoring all of the APIs it should.
- Test Your AI Tools with Simulations: The most effective way to determine the efficacy of your AI API security tool is to test them in real-time threat scenarios. Of course, you don’t want to wait for a malicious entity to attack your business. Instead, you can develop and simulate potential threats in your system and see how your AI API security tools respond to them.
- Prioritize Active Engagement: When creating an AI API security tool, you can either use it to focus on visibility enhancement and passive logging of potential threats or for reactive defense. Where possible, choose to use tools that can spearhead your defense system, initiating a threat response and beginning to isolate API threats where possible.
By incorporating these practices into your AI systems, your business will be better prepared to identify and eliminate zero day API vulnerabilities.
Maximize API Security with Check Point
Check Point is the #1 top performer in cybersecurity, leading the Miercom 2025 platforms assessment for AI-enabled cybersecurity support.
Check Point CloudGuard WAF uses contextual artificial intelligence tools to build up knowledge of your enterprise APIs and web applications. When it detects any strange signals or anomalies, it springs into action to stop attacks. Without the need to rely on signatures, CloudGuard is an all-in-one AI API security system.
CloudGuard WAF is just one of the advanced AI-enabled cybersecurity tools that Check Point offers. The Check Point Infinity ThreatCloud AI consolidates telemetry records and IoCs from millions of separate businesses and cybersecurity networks, developing a precise way of detecting both established and novel threats. From protecting against zero day threats to defending your company from leading cybersecurity attack vectors, Infinity ThreatCloud is an industry-leading solution.
Get started with Check Point today by reaching out for a demo.
