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InfoQ Homepage Articles API Security: from Defense-in-Depth (DiD) to Zero Trust

API Security: from Defense-in-Depth (DiD) to Zero Trust


Key Takeaways

  • Only a few companies have an API security policy that includes dedicated API testing and protection
  • Defense-in-Depth is a multi-layered defense that provides different types of protection: boundary defense, observability, and authentication
  • Authentication is the most important and can be achieved through password complexity, periodic modification, and two-factor authentication
  • To improve efficiency in security management, one can change from "finding bad people" to "identifying good people", by utilizing the allowlisting approach
  • Zero Trust is the next level for API security, though it is not a silver bullet

Stats of API Security

According to Salt Security's 2022 API Security Survey:

  • 95% of the more than 250 survey respondents said they’ve experienced an API security incident in the past 12 months
  • only 11% of respondents have an API security strategy that includes dedicated API testing and protection and 34% lack any security strategy at all for APIs
  • shift-left tactics are falling short, with more than 50% of respondents saying developers, DevOps, or DevSecOps teams are responsible for API security while 85% acknowledge their existing tools are not very effective in stopping API attacks
  • when asked about their biggest concern about their company’s API program, 40% of respondents highlighted gaps in security as their top worry
  • 94% of API exploits are happening against authenticated APIs, according to Salt customer data
  • stopping attacks tops the list of most valuable attributes of an API security platform
  • 40% of respondents are grappling with APIs that change at least every week, with 9% saying their APIs change daily

From the survey, we could see that nearly all companies have experienced API security incidents. However, only 11% of companies have an API security policy that includes dedicated API testing and protection.

So, what kinds of protection should a company build to defend against these attacks? Security problems are not unique to the Internet age. Over the last thousands of years of human history, various countries have been exploring and practicing multiple defense strategies and fortifications. These experiences and ideas are also applicable to the field of network security.

For example, WAF (Web Application Firewall) is analogous to castle walls, identity authentication is equal to the commanders’ ID card, and honeypots are used to lure attackers away from high-profile targets. Among these war strategies, one of the most effective methods is Defense-in-Depth (DiD).


Defense-in-Depth is a multi-layered defense strategy that provides different types of protection at each line of defense.

DiD can be roughly divided into three different key areas of defense:

Defending the Borders

Boundary defense is the most basic and common type of defense. Almost all companies invest in boundary defenses, such as WAFs, which use regular expressions and IP denylists to defend against known attack methods and security vulnerabilities.

Most of the so-called attacks are initiated by "script kiddies", relatively unskilled individuals who do not have strong technical backgrounds or hacker mindsets. They can only attack targets in batches by using pre-written scripts. In this scenario, boundary defense can well resist these indiscriminate attacks.

As the protection of the outermost layer, it has always been one of the necessary defense methods, though, from a technical point of view, WAF does not necessarily require strong technical skills.

In addition to WAFs, some defense tools are explicitly designed for bots. Using bots to carry out "credential stuffing" attacks is a standard method to attempt to steal high-value digital assets. The strategy is to buy login information, such as leaked emails/passwords, and then attempt to log in to other websites in batches. The most efficient defense method to combat credential stuffing is to identify the bot and intercept all requests made by the bot.

The basic strategy behind bot interception is a defense tool deployed between the server and client acting as an intermediary. When the server returns a response page, the tool inserts JavaScript into that response. It requires the client (browser or bot) to execute the JavaScript to calculate the token and put it into the cookie. After the tool receives the token, it will judge whether the other party is malicious based on the token value and take corresponding actions. It can also encrypt specified page contents (such as the URL on the page or the content of the form).

Although, in theory, this kind of encryption is not difficult for a determined cryptography enthusiast (because a perfect key establishment mechanism is not implemented between the client and the server), it is enough to stop hackers with penetration tools.

In an enterprise server-side architecture, the WAF, SSL gateway, traffic gateway, and API gateway are all connected in series, with upstream and downstream relationships. Each can be deployed separately or combined into one component. Take Apache APISIX as an example: it provides some standard features for boundary defense: IP allowlists and denylists, a WAF rules engine, fault injection, and rate limiting. When used in combination, it can block almost all indiscriminate attacks.

Detecting Intruders

In network security, the scariest event is not actually finding a security incident, but never finding one. The latter means that you may have been hacked many times without realizing it.

Being able to observe security risks is critical in combating targeted attacks. After a hacker has breached the outermost layer of defenses, we need observability mechanisms to identify which traffic is likely the malicious attack traffic.

Common means of implementing security observability are honeypots, IDS (Intrusion Detection System), NTA (Network Traffic Analysis), NDR (Network Detection and Response), APT (Advanced Persistent Threat), and threat intelligence. Among them, honeypots are one of the oldest methods. By imitating some high-value targets to set traps for malicious attackers, they can analyze attack behaviors and even help locate attackers.

On the other hand, APT detection and some machine learning methods are not intuitive to evaluate. Fortunately, for most enterprise users, simple log collection and analysis, behavior tracking, and digital evidence are enough for the timely detection of abnormal behaviors.

Machine learning is an advanced but imperfect technology with some problems like false or missed reports. However, most enterprises don’t currently need such solutions. They care more about logs collecting and tracking because they need to collect digital evidence. Digital evidence not only serves as evidence of the crime but also helps companies better understand the weaknesses of their internal systems.

For example, when a hacker attacks a system and steals data, a behavior tracking solution would track a number of things including: when the hacker attacked, which servers were accessed, which data has been exfiltrated, and how the hacker behaved within the environment. These access logs can be found and gathered as digital evidence.

At the observability level, Apache APISIX can do more things than tracing, logging, and metrics. It can use plugins to simulate high-value targets to confuse the attackers, utilize the traffic mirroring functionality to send partial requests to the blocking and non-blocking security detection tools for analysis, and make quick security decisions to stop the attack.

Preventing Lateral Movement

When the attacker breaks through the outer defense line and enters the intranet, it is time for authentication and access control to play a role. This defense method is similar to showing your ID cards to purchase alcohol and your passport at the airport checkpoint. Without the corresponding identity and authority, it is impossible to enter the corresponding system.

This line of defense reflects a company's basic security skills and technical strength. Many companies' internal systems do not have well-established authentication and authorization architecture, and implementing those solutions requires long-term and continuous investment.

For example, numerous systems have been used for years in financial institutions, such as banks, securities, and insurance companies. The significant number of employees and legacy systems requires a high cost in both time and money to unify the identity authentication by implementing SSO (Single Sign-On).

This line of defense essentially puts obstacles everywhere for the attackers, making it impossible for them to move laterally within the network.

It is worth mentioning that there are not many companies that do well in seemingly simple password management. Password complexity, mandatory periodic modification, and mandatory two-factor authentication (SMS or dynamic password) for critical systems are easier said than done. Only companies who understand network security well can implement them well. There are a number of reasons why this is true but the key reasons include:

  • Many companies pay insufficient attention to password management because they believe that they are only effective within the internal network, which is relatively safe.
  • It will burden the IT department if companies conduct regular secret changes because there are many employees whose secrets are different, which is hard to manage.
  • Unless the policy is required at the company level, implementing consistent and effective secret management is challenging.

This third line of defense is the most important one. Boundary protection and security threat observation, to a large extent, exist to help the third line of defense. If an application system itself is not safe, no matter how strong the first two lines of defense are, there will be attacks that slip through the net.

This line of defense is where an API Gateway comes in strong as it provides a number of key authentication features:

  • Various authentication methods, such as JWT and key auth
  • Integrating with multiple authentication systems such as OKTA and Auth 2.0
  • TLS and mTLS encryption of traffic
  • Automatic rotation of keys

In summary, these three defense layers require inter-department cooperation to block security attacks effectively. These three defense layers are typically controlled by different departments: WAF by the Security Operations team, observability by the R&D teams, and authentication by the IT department. Each area will use different tools, such as WAFs, OpenTelementry, and Keycloak, to implement their respective solution. This split of responsibility across many teams is why effective blocking requires inter-department cooperation.

So, is there a more efficient way, the so-called "silver bullet," to solve all security problems?

From "Denylisting" to "Allowlisting"

The network security community has been thinking about this issue for a long time. The strategy for most security defense and detection methods is to look for a small number of security threats within a massive quantity of data, similar to finding a needle in a haystack. There will inevitably be both false positives and false negatives.

What if we change our thinking and turn "finding bad people" into "identifying good people"? Will it help us shine a new light on the problems?

Over ten years ago, some antivirus software companies began to make such an attempt. Their logic was to add the commonly used software to an allowlist, identifying the executable programs one by one, and then the rest would be viruses. In this case, any new virus could not escape the detection of antivirus software. This plan was quite ideal. Nevertheless, it took four or five years for the software companies to implement it, and it was not entirely allowlisting but hierarchical management.

The allowlisting approach is equally applicable in API security. For example, a company provides a payment API interface, which requires a token to access. If there is no token or the token cannot properly be accessed, then it must be a malicious request and needs to be rejected directly.

Ideally, all APIs should have similar authentication and access controls, and only authenticated access is allowed. Although this cannot defend against internal threats, social engineering, and 0-day attacks, it will significantly increase the threshold of attacks, making the cost high and indiscriminate attacks impossible.

For attackers, when the ROI (Return on Investment) becomes unreasonable, they will immediately turn around and look for other easy-to-break targets.

Based on the ideas of defense in depth and allowlisting, a "zero trust" security framework has gradually evolved, hoping to solve network security problems once and for all.

Is Zero Trust the Silver Bullet for API Security?

What is Zero Trust? Put simply: there is no trusted client in the system, so you will need to verify your identity everywhere.

Whether it is an external request or internal access, a bastion or a springboard, a mobile phone or a PC, an ordinary employee or a CEO, none can be trusted. Access to systems and APIs is allowed only after authentication.

It seems that there are no loopholes except that it is troublesome to verify the identity everywhere. So is zero trust the silver bullet for cybersecurity?

Simply put: no, zero trust is not a silver bullet.

Zero trust is a comprehensive security framework and strategy. It requires adding strict and unified identity authentication systems to all terminals, BYODs (Bring Your Own Devices), servers, APIs, microservices, data storage, and internal services. Think of zero trust as a safety air cushion. We can understand the zero trust model by using the Wooden Bucket Theory, which states that a wooden bucket can only hold as much water as its shortest plank. Translating this to security, our defenses are only as good as our weakest spot. This implies that the hacker will always attack the weakest part. If the bucket leaks, it doesn't matter how much water it could hold. However, we also can’t say, "90% coverage of a zero trust model is not substantially better than 0% coverage" because the measures can increase the cost of hackers’ attacks. If we can realize 90% coverage of a zero trust model, then almost 80%-90% of vicious attacks could be intercepted.

The implementation of zero trust is complicated. Imagine adding identification equipment in all transportation hubs, such as airports and high-speed railways. It is incredibly costly in terms of time and money.

In a large enterprise, there will be hundreds of systems, tens of thousands of APIs and microservices, and hundreds of thousands of clients. It takes great effort and cost to build a complete zero-trust system. Therefore, zero trust is mainly implemented in government, military, and large enterprises. For most enterprises, it is wiser to learn from the idea of zero trust and build a security defense system with a higher ROI.

There are two core components of Zero Trust:

  • Identity and Access Management
  • API Gateway with integrated security

The focus on these two components can make the implementation of zero trust more realistic.

Note here that zero trust is not flawless. Zero-trust solutions cannot fully defend against zero-day or social engineering attacks, although they can greatly reduce the blast radius of those attacks.


However, security is a never-ending game of cat and mouse because attackers are always hoping to find means to acquire high-value digital assets or to achieve their destructive outcomes. Defense alone cannot avoid the attacker’s guns and arrows.

Consequently, it is also necessary to improve the security awareness of developers and reduce exposure to vulnerable surfaces as much as possible.

Developers stand in the middle of code and application. On the left is the “code”, while on the right is the “application”. Hence we need to pay more attention to the left side as the code is the root of all the problems. We should adopt the “shift left” method, which means a DevOps team needs to guarantee application security at the earliest stages in the development lifecycle. The vulnerable exposure can be significantly reduced if the developers improve their security awareness.

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