Explore the importance of identifying secrets in code, and how early detection can prevent data breaches.
Application security (AppSec) is far from new, first emerging as a formal discipline in the late 1990s and early 2000s when web adoption surged. As reliance on web applications has grown, so has the role AppSec plays in protecting digital assets. One important way web applications are protected from unauthorized access, data breaches, and other security threats is through the use of secrets, which serve as the credentials and keys that enable secure communication, authentication, and data protection. Unfortunately, secrets often end up in code, handing attackers the keys to access sensitive information.
Let’s examine secrets exposure risk; why it’s important to identify leaked credentials, APIs, tokens, and hardcoded secrets; and how automated secrets detection can lead to early detection and prevent data breaches.
Secrets Embedded in Code: How It Happens
Secrets, such as API keys, database credentials, tokens, and encryption keys enable applications to connect with external systems and services, but they often find their way into code during software development. As one example, a security researcher recently found at least 15,000 developer secrets hardcoded into software. One of the biggest reasons, and perhaps easiest to understand, is developer convenience — developers hardcode secrets to make it easier to do local testing and debugging during development, ensuring that software vulnerabilities are addressed early in the software development lifecycle (SDLC), before the software enters runtime.
What often results, though, is that the developer may forget that the secret is hardcoded, inadvertently increasing the risk of compromise from this risky practice. What’s more, some developers may be unaware of the risks involved in embedding secrets directly in code and fail to remove them. When that code is committed to version control systems, those secrets become available to anyone with access to the repository, exposing them to potential attackers.
Part of the problem may be that developers don’t have a secure place to store credentials, so their only option is to embed the secrets directly into the source code. Sometimes, development teams are under tight deadlines that deprioritize security requirements in favor of delivering new functionality quickly.
This problem has received more attention in recent years; according to the 2024 Thales Data Threat Report, 56% of respondents indicated that secrets management is their top DevOps challenge in identifying emerging risks.
Exposed Secrets Increase Risk
The unfortunate reality, though, is that attackers commonly use automated secrets scanning on public repositories to exploit misconfigured private repositories, analyze leaked source code, and reverse engineer applications to identify and extract hardcoded secrets. These exposed secrets can result in serious consequences, including unauthorized access to sensitive data, compromised systems, and financial losses, not to mention, compliance violations and widescale data breaches, such as the GitHub Action breach, which continues to cause damage long after the initial attack.
Why Early, Comprehensive Secrets Detection Is Needed
Detecting secrets in code early is an important part of data breach prevention because it helps maintain strong security practices, minimize risks, and protect sensitive digital assets. For a long time, security professionals have been advocating a shift-left approach to security in software development. This approach integrates security processes and testing early in the software development lifecycle (SDLC) rather than addressing security concerns during deployment or post-production, where issues are both more difficult and more costly to remediate. However, unless you’re including secrets detection early on, you’re missing an important aspect of securing the SDLC.
Early detection of secrets is important for many reasons, including:
- Prevent unauthorized access and data breaches: Secrets embedded in code can be exploited by attackers to gain unauthorized access to systems, databases, APIs, or cloud services. These secrets provide entry points for attackers to access sensitive data, resulting in data breaches that compromise personal information, intellectual property, and financial records, potentially resulting in service disruptions, regulatory fines, and reputational harm.
- Stop secrets from entering version control: Once secrets are committed to a version control system, they become part of the repository’s history. Even if removed later, they can still be recovered unless the repository history is purged. Early detection stops secrets from being committed in the first place.
- Reduce remediation costs: Fixing security issues becomes more expensive as they progress through the SDLC. Industry studies show vulnerabilities detected during development cost significantly less to remediate than those discovered in production.
- Prevent propagation through CI/CD pipelines: Hardcoded secrets can spread through automated build and deployment pipelines, becoming embedded in production environments, logs, or configuration files.
- Maintain regulatory compliance: Many compliance regulations (such as GDPR and HIPAA) require organizations to use software security best practices such as safeguarding sensitive data. Secrets exposed during development could lead to non-compliance if not addressed before deployment.
What’s Needed: Comprehensive Secrets Management
Often, AppSec teams understand why secrets detection is important but rely on manual code review to identify hardcoded secrets. Instead of this resource-intensive and impossible-to-scale method, AppSec teams need an easy way to identify active secrets present in code, prioritize those secrets based on the severity of risks and version histories, and then monitor for and identify suspicious behavior even after secrets have been removed. That means you need a solution that:
- Assess CI/CD security posture: Run security policies across your CI/CD pipelines to prevent misconfigurations and detect leaked credentials. This automates compliance and detects secrets early on, improving developer productivity without impacting velocity.
- Scan for secrets: Check for any compromised passwords, API keys, tokens, or other credentials in your delivery pipelines before they become exposed to public repositories.
- Analyze container security: Check for hardcoded secrets in your source code and vulnerabilities in Kubernetes workloads and Docker container registries and images.
- Evaluate cloud security: Identify any insecure APIs and cloud misconfigurations early in the SDLC.
- Protect production integrity: Enforce security policies from design to runtime by automatically identifying unintended components to ensure only trusted builds reach production.
Secrets Detection as Part of Your AppSec Strategy
Secrets detection is an important aspect of AppSec that’s easy to overlook, but it’s a part of building a robust security strategy. You can significantly reduce the risk of data breaches by identifying and remediating secrets, API keys, tokens, and potentially even passwords within codebases. Early detection of hardcoded and exposed secrets is an important part of a strong application security program. Solutions offering comprehensive coverage in a single dashboard can help your organization significantly improve its security posture and protect digital assets from potential data breaches and other cybersecurity threats. In short, focusing on secrets management will help you and your team:
- Enhance AppSec secrets management: Implement robust secrets detection tools for greater prioritizations and accuracy.
- Prevent data breaches: Utilize API key scanning and credential scanning to stop sensitive data leakage.
- Improve CI/CD pipeline security: Integrate hardcoded secrets detection early in the SDLC.
- Empower developers: Provide developer-friendly secrets detection tools that help developers focus on the risks that matter.
- Strengthen application security posture: Proactively detect and manage secrets to minimize cyber risk exposure.
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