Ethical Hacking News
Exposing the Gaps in Secrets Detection: A Deep Dive into Vulnerabilities in JavaScript Bundles
Traditional vulnerability scanners struggle with detecting secrets in modern applications due to limitations in regular expression coverage.Sensitivity information, such as authentication tokens and API keys, often remains hidden from users but can be present in application code.Existing secrets detection methods have clear limitations, including inability to detect secrets within JavaScript files or assets.Dynamic Application Security Testing (DAST) tools are more robust but have higher costs, in-depth configuration requirements, and limited regular expression coverage.Static Application Security Testing (SAST) tools analyze source code for vulnerabilities but can miss certain types of exposures.A recent study found over 42,000 exposed tokens across 334 different secret types in approximately 5 million applications.The importance of single-page application spidering in catching secrets before they reach production is highlighted.Organizations must adopt a comprehensive approach to application security testing, incorporating both static and dynamic analysis.
The world of cybersecurity is constantly evolving, and one area that has seen significant advancements in recent years is application security testing. However, despite these efforts, a crucial gap remains in the detection of sensitive information within JavaScript bundles. This article aims to shed light on this issue, exploring the limitations of existing secrets detection methods and highlighting the importance of single-page application (SPA) spidering in catching secrets before they reach production.
In today's digital landscape, applications are often built using complex technologies such as JavaScript, which can contain sensitive information that is not immediately apparent to the average user. This information can range from authentication tokens to API keys, and even project management data. However, despite the growing importance of application security testing, many organizations still fall victim to these types of attacks.
To understand the scope of the issue, it is essential to examine existing secrets detection methods. Traditional vulnerability scanners rely on a set of known paths and regular expressions to match known secret formats. While this approach can be effective in catching some exposures, it has clear limitations. For instance, Nuclei's GitLab personal access token template demonstrates how traditional vulnerability scanners can struggle with modern application architectures.
Nuclei's GitLab personal access token template is a prime example of the challenges faced by traditional vulnerability scanners. When provided with a base URL, such as https://portal.intruder.io/, the scanner makes an HTTP GET request to that single page and attempts to identify the pattern of a GitLab personal access token. If found, it then makes a follow-up request to GitLab's public API to check whether the token is active. This approach may seem straightforward, but it has significant limitations.
One major issue with this traditional approach is its inability to detect secrets within JavaScript files or assets. When the scanner is given a base URL, subsequent requests that would be made by a browser, such as the JavaScript files required to render the page (e.g., https://portal.intruder.io/assets/index-DzChsIZu.js), will not be made using this old-school approach.
In contrast, Dynamic Application Security Testing (DAST) tools are generally more robust and can perform full spidering of applications, support for authentication, and a wider range of detection capabilities. However, these tools have their own set of limitations, including higher costs, in-depth configuration requirements, and limited regular expression coverage compared to well-known command-line tools.
Static Application Security Testing (SAST) tools, on the other hand, analyze source code to identify vulnerabilities and are often used as a primary method for detecting secrets before code reaches production. While SAST is effective at catching hardcoded credentials and preventing some classes of exposure, it also has its limitations.
The authors of the study discovered that SAST methods do not cover the full picture, and once again, some secrets within JavaScript bundles slipped through the gaps in static analysis. This realization led the researchers to build an automated check for scanning approximately 5 million applications and examine the output.
The results were striking, with over 42,000 exposed tokens across 334 different secret types identified. The majority of these exposures came from code repository platforms such as GitHub and GitLab, where tokens for private repositories were left unattended. Another significant exposure involved an API key for Linear, a project management application, embedded directly in front-end code.
The study's findings highlight the importance of single-page application spidering in catching secrets before they reach production. By combining traditional vulnerability scanners with DAST and SAST tools, organizations can significantly improve their overall security posture. However, this approach requires a proactive mindset and a willingness to invest time and resources into staying ahead of emerging threats.
The authors conclude by emphasizing the need for shift-left controls, such as repository scanning, SAST, and IDE guardrails, but also recognize that secrets introduced during build and deployment can bypass these safeguards and end up in front-end code. To mitigate this risk, organizations must adopt a more comprehensive approach to application security testing, one that incorporates both static and dynamic analysis.
In summary, the study highlights the limitations of existing secrets detection methods and underscores the importance of single-page application spidering in catching sensitive information within JavaScript bundles. By recognizing these gaps and adopting a proactive approach to application security testing, organizations can significantly reduce their exposure to cyber threats and protect their digital assets from harm.
Related Information:
https://www.ethicalhackingnews.com/articles/Exposing-the-Gaps-in-Secrets-Detection-A-Deep-Dive-into-Vulnerabilities-in-JavaScript-Bundles-ehn.shtml
https://thehackernews.com/2026/01/why-secrets-in-javascript-bundles-are.html
https://www.intruder.io/research/secrets-detection-javascript
Published: Tue Jan 20 06:02:02 2026 by llama3.2 3B Q4_K_M
