Secrets detection is essential, as they (secrets) are the key to controlling access to confidential systems, authenticating resources, and building secure applications. They’re also an attractive target for malicious actors who seek them out to exploit them. We’ve seen this in recent breaches that affected Microsoft and Uber.
The consequences of secrets leaked by threat actors are far-reaching, costing organizations $1.2 million in revenue on average. Management and detection are top priorities for security teams and developers. But it’s a tightrope to walk: organizations must leverage what is essential, while simultaneously mitigating potential risks.
In this article, we explore secrets detection in detail, including challenges, best practices, and tools that’ll help you keep your most sensitive data safe. First, let’s clarify what exactly secrets are.
Key Takeaways:
- Secrets such as API keys, passwords, and encryption keys are essential for accessing sensitive systems and data. Exposing these secrets can lead to breaches, financial losses, and compliance violations, making their detection a top priority for security teams.
- Detecting secrets can be difficult due to false positives, limited coverage, and the complexity of managing multiple security tools. Integration with CI/CD pipelines, alert fatigue, and collaboration between security and development teams also add to the challenge.
- Key best practices include implementing pre-commit hooks, integrating secrets scanning throughout the SDLC, rotating secrets regularly, educating developers on secure coding, and taking a platform approach rather than relying on isolated tools. These strategies help ensure comprehensive protection and reduce the risk of secrets exposure.
What Are Secrets?
In the digital world, secrets are sensitive pieces of information that organizations don’t want publicly exposed. If they were in a physical folder, it’d be marked ‘CONFIDENTIAL’ and locked away in a filing cabinet. While the vast majority are authentication related, that’s not a qualifying characteristic.
Here are a just few examples of secrets:
- Usernames and passwords
- Encryption keys
- API keys
- Tokens and sessions IDs
- Private keys
- Digital certificates
- Biometric data
- Configuration files
- Personally identifiable information (PII)
Regardless of the type of secret, they’re intended to be secured from unauthorized access, because they are an incredible security risk.
Why Leaked Secrets Are a Security Risk
A compromised Netflix password doesn’t pose the same security risk as an encryption key for a database. One might expose embarrassing viewing history, while the other could expose customer data.
In the case of the latter, secrets can be used to gain unauthorized access to systems, applications, and sensitive data. Lateral movement exacerbates existing attacks and, because authentic credentials are used, they’re harder to detect, take longer to contain, and the consequences are greater. This includes Separation of Duty (SoD) violations.
Of course, secrets only become dangerous when they’re exposed to attackers. So, how does that happen? Leaks generally happen in one of three ways:
- Compromised accounts: Whether via phishing, brute force attacks, or another tactic, bad actors can compromise an account, move laterally throughout the SDLC, and gain access to code that has secrets in it. While compromising accounts isn’t a new exploit, developers have become even higher value targets due to the level of access their accounts now provide, particularly when it comes to code repositories, logs, and configuration files.
- Malicious insiders: Someone with legitimate access to a system could abuse their privileges to alter code, change access controls, or obtain and leak sensitive information.
- Source code leak: It’s surprisingly easy to leak code accidentally. Code could be committed to the wrong repo, or a misconfiguration could lead to faulty access controls. Either way, if it ends up in the public domain, and it has secrets in it, attackers can worm their way into protected systems.
Dangers of Secret Exposure
There’s a lot at stake when secrets are compromised. For example:
- Data Breaches: When attackers obtain and exploit secrets, they can potentially gain access to a vast amount of sensitive information, including personal data and intellectual property like source code and trade secrets. As we’ve learned from high-profile breaches, the consequences include financial loss, reputational damage, loss of customer trust, and – especially in the case of exposed intellectual property – a diminished competitive edge.
- Financial Loss: In addition to the financial loss caused by a data breach (which has climbed to $4.45 million on average according to IBM’s annual Cost of a Data Breach report), compromised secrets like bank credentials can be used to conduct fraudulent transactions, leading to significant losses for individuals or organizations.
- Unauthorized Operations: Attackers with access to secrets may manipulate data, elevate privileges, or disrupt services. This includes compromising the software a vendor provides to customers, which, as we saw in the SolarWinds attack, can have significant consequences. This is especially the case in critical infrastructure or financial systems.
- Account Hijacking: Attackers may use stolen credentials to hijack user accounts. This can lead to the unauthorized access, manipulation, and even deletion of user data.
- Compliance Violations: Certain industries and most regions have specific regulations and compliance requirements regarding the protection of sensitive information. Compromised secrets can lead to violations of these regulations, and subsequent legal consequences and fines.
To mitigate these risks, organizations have started to prioritize DevSecOps and continuous integration, necessitating the implementation of robust practices that minimize the risk of secret exposure. This includes encryption, access controls that follow the principle of least privilege, secure storage practices, rotation policies, and multi-factor authentication.
But this doesn’t account for human error, supply chain risks, or incorrectly implemented encryption. That’s why security teams leverage secret detection.
What Is Secrets Detection?
Secrets detection is an automated process that scans code and configurations for patterns and formats indicative of sensitive information. To ensure comprehensive coverage, detection should be integrated into continuous integration and continuous deployment (CI/CD) pipelines and these should be scanned:
- Source Management Control (SCM) tools
- Version histories
- Public and private repositories
- Delivery pipelines
- Kubernetes resources
- Containers
- Productivity tools like Slack and Confluence
The goal is simple: Early detection and mitigation of secret leaks. Importantly, this strategy doesn’t eliminate the need for robust security and development practices. It’s a vital additional layer of defense.
How Do Secret Detection Tools Work?
Secrets detection tools employ a multi-layered approach to sniff out hidden secrets lurking in your code.
- Pattern Matching: Pattern matching algorithms can be used to search for known patterns or formats of sensitive information. For example, they might look for strings that match the typical structure of API keys, passwords, or other credentials.
- Regular Expressions: Regular expressions can also be used to define patterns that match specific types of secrets, allowing for flexible and customizable search criteria.
- Entropy Analysis: Some advanced secret detection tools use entropy analysis to identify sequences of characters that exhibit characteristics of random or encrypted data. This can help uncover potential secrets, even if they don’t follow standard patterns.
- Dictionary-Based Detection: Dictionaries or predefined lists of known sensitive terms or keywords can also be used to help identify common names or phrases associated with secrets.
- Artificial Intelligence (AI) and Machine Learning (ML): More recently, AI and ML have been used to automate and improve the accuracy of secret detectors. Models can be trained on large datasets to recognize patterns, sequences, and anomalies associated with sensitive information.
When a potential leak is detected, these tools typically generate alerts or reports to inform developers or security teams. Once identified, organizations can take steps to secure or rotate the exposed secrets and improve their overall security posture.
Easy, right? Not quite.There are several factors that make detecting secrets and management an uphill battle, even with these tools.
Challenges of Secret Detection And Management
Limited Coverage
Regular expressions, dictionary-based detection, and pattern matching all rely on predefined lists, which may not encompass all possible variations and permutations of sensitive information, especially in dynamic environments where data changes frequently. Attackers can easily devise new terms or use obfuscation techniques to evade detection.
Tool Sprawl
The average organization uses 50+ security tools across their developer and security teams, according to our 2025 State of ASPM report, often involving a mix of on-prem and cloud-based systems.
While these tools were implemented to help fortify defenses, the proliferation of AppSec tools is overwhelming the very people tasked with managing them. In fact, 4 out of 5 security professionals say they find managing multiple different security tools challenging.
Unsurprisingly, the more tools an organization uses, the more likely they are to be concerned about gaps in visibility.
Managing Secrets in a Multi-Cloud Environment
Some organizations rely on multiple cloud providers to avoid vendor lock-in, distribute workloads, and improve performance.
But because different cloud providers’ may have their own native solutions for managing secrets, it can be difficult to develop a unified approach. Similarly, ensuring consistent security practices across multiple clouds (especially with different security models and compliance requirements) can be complex and challenging, with a lot of operational overhead.
Alert Fatigue and False Positives
Security detection generates alerts for potential security incidents or policy violations. Now, imagine the number of alerts teams are bombarded with when nearly 50+ tools are under their purview. So many alerts (many of which are likely false positives) can lead to alert fatigue. On a good day, this just makes it more challenging to identify and prioritize genuine security threats. On a bad day, it may cause security and developer teams to overlook or ignore alerts, potentially allowing real security incidents to go unnoticed.
Integration with CI/CD Pipelines
CI/CD pipelines are designed for rapid and continuous software development, testing, and deployment. But security measures often introduce additional steps or checks that can slow down the pipeline, contradicting the goal of agility. The result? Developers bypass, neglect, or ignore them.
Which brings us to our final challenge…
Collaboration Between Security and Dev Teams
Developers are under pressure to deliver innovative solutions, and fixing security issues isn’t their primary job. That means that, when security hands alerts to developers with little or no context, it stresses an already strained relationship.
It’s no wonder our research shows 74% of security professionals say the relationship between security and developers needs to improve.
The secret (get it?) to a more collaborative and effective relationship? A detection and management tool that meets the unique requirements of both security teams and developers. That means it must provide clear visibility of all attack vectors, minimize alert fatigue, and seamlessly integrate into developer workflows.
There’s only one solution, and it’s called Application Security Posture Management (ASPM).
Best Practices for Detecting Secrets
As we’ve said, detecting secrets within your codebase is essential, but it comes with its challenges—false positives, full coverage, and seamless integration with existing workflows. Here are the top best practices that can help you overcome these challenges and ensure sensitive information stays secure.
- Implement Pre-Commit Hooks: Pre-commit hooks are one of the most effective tools for preventing secrets from entering your codebase. By running automated scans on your code before it’s committed to version control, you can catch secrets early and reduce the chances of them ever reaching production. This proactive approach helps stop leaks before they start.
- Integrate Secrets Scanning Throughout the SDLC: Secrets scanning should be an ongoing process, not a one-off. To ensure continuous protection, integrate secrets scanning into every phase of the SDLC—from development to production. By doing so, you catch secrets wherever they may appear, providing comprehensive coverage across environments and reducing the risk of exposed data.
- Regular Secret Rotation Strategies: To minimize the impact of any exposed secrets, establish a routine for rotating API keys, passwords, and other sensitive data. Regular rotation ensures that even if secrets are exposed, they become obsolete quickly. This practice strengthens your security posture by limiting the potential window of exposure.
- Developer Education and Training: One of the best ways to prevent secrets leaks is by empowering your developers. Provide regular training on secure coding practices, the risks of hardcoding secrets, and how to use secure storage solutions. An informed team is key to reducing human error and fostering a culture of security.
Take a Platform Approach vs. Point Solutions: Instead of relying on isolated tools for secrets detection, opt for a platform approach that integrates secrets scanning with other security functionalities. This unified approach offers better visibility, streamlines workflows, and ensures that secrets management aligns with your overall security strategy, providing comprehensive protection across your development lifecycle.
Get Complete Peace of Mind with Cycode ASPM
Cycode’s security-first, developer-friendly ASPM platform provides visibility, prioritization, and remediation to help security, engineering, and DevOps teams detect and manage secrets.
Prevention
There are a few crucial steps organizations should take to prevent secrets from making their way into code in the first place. Developers should implement regular reviews, follow the principle of least privilege, and use encryption to ensure sensitive information remains secure when being transferred over networks.
Secret management tools can also help and, with Cycode’s ASPM, you can bring multiple tools together in one view to ensure secrets are securely stored and managed.
Visibility
The breadth and depth of Cycode’s end-to-end scanning capabilities enables security teams and developers to find API keys, tokens, proprietary information, and other secrets, even those that aren’t hidden in source code. This includes build logs, infrastructure, Kubernetes clusters, version history, and even collaboration tools like Slack and Confluence.
Users are promptly notified of public source code exposure, and workflows can be used to send alerts, create tickets, and automatically resolve the leak of private resources.
Have unique requirements? Cycode supports custom secrets and policies, too.
Prioritization
Not all secrets are created equal. That’s why Cycode automatically helps teams prioritize remediation with customer risk scoring based on criticality, location, and likelihood of secret exposure. This ensures developer efforts are focused where they will be most impactful so they can reduce risk and get back to writing code.
Remediation
Cycode’s developer-friendly workflows make it easier than ever to enforce coding best practices and stop secrets before they enter your codebase. The platform also offers developers the tools they need to find and fix source code leaks in their native environment. That’s right. Cycode isn’t just another tool developers have to adopt, with another dashboard to check.
Want peace of mind that your data are safe? Book a demo now to see how Cycode can enhance your secrets detection capabilities.
