Secret Scanning: A Critical Practice for Protecting Sensitive Data in Code

With the rise of CI/CD pipelines, cloud-native development, and globally distributed teams, sensitive credentials like API keys, tokens, and database passwords often slip into source code. Sometimes accidentally, sometimes under pressure to deploy fast.

This is not a rare mishap. A recent study found that 34% of API security incidents involve sensitive data exposure. And according to Cyble, over 1.5 million .env files containing secrets have been discovered in publicly accessible environments.

Leaked credentials are often exploited within minutes, enabling attackers to access cloud storage, spin up crypto-mining servers, or exfiltrate sensitive data.

In this growing threat landscape, secret scanning is essential. It helps detect and remove exposed secrets before attackers find them, reducing the risk of breaches, data loss, and infrastructure compromise.

What are Secrets in Code?

Secrets are sensitive pieces of information that should remain confidential. When embedded in code repositories, they pose a serious security risk.

Examples of Secrets:

• API keys (e.g., AWS, Stripe, Twilio)
• OAuth tokens
• SSH private keys
• Database credentials
• JWT signing secrets
• TLS/SSL certificates
• Encryption keys
• Cloud provider access keys

Hardcoding these values or including them in configuration files can expose them to version control systems like Git, where they may inadvertently be shared or pushed to public repositories.

What is Secret Scanning?

Secret scanning is the automated process of detecting secrets (like keys or passwords) that are accidentally included in source code, repositories, or configuration files.

It is designed to:

• Prevent secret leaks before code is pushed to production.
• Alert developers and security teams about exposures.
• Reduce the attack surface by enforcing proper credential handling.

Secret scanning can be integrated into local development environments, CI/CD pipelines, and repository monitoring tools to ensure secrets do not slip through undetected.

Why Secret Scanning Is Critical

The importance of secret scanning cannot be overstated. A single leaked API key can give attackers access to:

• Your cloud infrastructure (e.g., AWS S3 buckets)
• Customer PII or financial data
• CI/CD environments
• Internal services and source code
• Third-party integrations

Without secret scanning, these risks remain invisible until exploited.

How Secrets Get Exposed in the First Place

Secrets typically find their way into code during the chaos of development. Developers working under tight deadlines may embed credentials to speed up testing, enable certain features, or integrate third-party services. These might be overlooked or forgotten by the time the code goes into production.

In some cases, staging and production environments share the same configuration files or credentials, increasing the risk of sensitive information ending up in live user-facing code. APIs used in front-end logic may also carry authentication tokens in headers or as part of JavaScript bundles.

Furthermore, tools used for error tracking, analytics, and debugging can unintentionally leak sensitive environment variables or data in payloads. Over time, these practices accumulate and expose the organization to significant risk.

Common Sources of Secret Exposure

• Hardcoded credentials in codebases during development
• Configuration files checked into version control (.env, config.json)
• Developer notes or comments accidentally committed
• Debug logs that capture runtime secrets
• Copy-pasting keys in shared channels or documents
• CI/CD environment variables exposed in build logs

Even if secrets are rotated regularly, their exposure even for a short time can lead to major breaches if attackers act quickly.

The Impact of Exposed Secrets

The consequences of leaked secrets are both immediate and severe. In the past year, 83% of organizations experienced at least one security incident linked to hardcoded secrets (Thales Group, 2024).

These breaches are not just technical slip-ups they come with a high price tag. On average, incidents involving exposed secrets cost organizations $4.5 million per breach, factoring in operational downtime, regulatory penalties, and remediation efforts (IBM Cost of a Data Breach Report, 2024).

Exposed secrets can allow:

• Unauthorized Access to Systems: Cloud provider credentials embedded in JavaScript can be used to access S3 buckets, databases, or even execute privileged operations via APIs.
• Privilege Escalation: Hardcoded JWT signing secrets or static tokens can allow attackers to forge valid tokens, impersonate users, or bypass authentication mechanisms.
• Service Disruption and Data Loss: API keys exposed in the frontend can be misused to delete data, exhaust usage quotas, or trigger service outages.
• Internal Reconnaissance: Leaked internal hostnames, IPs, or references to private infrastructure components can provide attackers with a blueprint of the internal network, easing lateral movement during an attack.

Each exposed secret represents a potential entry point into your system. The more critical the secret, the more devastating the impact.

Real-world breaches highlight the growing risk:

• Unit 42 Analysis (2024): A scan of publicly accessible .env files revealed 1,185 exposed AWS keys across 110,000 domains, illustrating the scale of unattended secret leaks.
• Football Australia (2024): Leaked credentials enabled unauthorized access to 127 storage repositories, exposing player contracts, passport details, and customer purchase records.
• Schneider Electric (2024): Hackers used exposed credentials to steal 40GB of sensitive data, including names and email addresses of over 75,000 employees and customers.
• GitHub Repositories (2021): Security researchers discovered over 100,000 public repositories containing at least one exposed credential, token, or API key, highlighting widespread mismanagement of secrets in code.

How Indusface Help You Discover and Remediate Exposed Secrets

Indusface combines the power of its experienced security services team with advanced analysis techniques to tackle one of the most overlooked threats in modern applications: Secrets unintentionally embedded in publicly accessible code.

To proactively address this challenge, Indusface follows a structured, expert-led approach that blends automation with human insight. This ensures accurate detection, contextual understanding, and actionable remediation.

Here is how the process unfolds:

Step 1: Target Mapping

The first step involves the complete discovery of exposed digital assets. Indusface’s security experts identify all relevant application endpoints and public-facing resources across production, staging, and QA environments. This includes not only primary domains but also subdomains, microservices, and legacy components that might still be alive.

All files and scripts accessible via the browser or client interface are mapped to. This helps the team build a comprehensive inventory of code that could potentially contain embedded secrets, setting the stage for deeper inspection.

Step 2: Source Code Inspection

Once target assets are mapped, the team performs a detailed inspection of the codebase. This includes analyzing HTML, JavaScript, and any associated configurations or scripts served to clients.

The code is normalized to simplify and clarify its structure, allowing security analysts to extract logic, variables, encoded strings, and configuration blocks. Special attention is paid to areas where developers might have embedded test data, temporary keys, or integration credentials.

This process enables the team to identify hidden data structures or values that do not stand out on the surface but could carry significant risk.

Step 3: Secret Pattern Extraction

With the code structure in place, the team initiates a comprehensive scan for potential secrets. Analysts look for patterns such as:

• High-entropy strings that resemble tokens or keys
• Plain-text username-password combinations
• Encoded values in base64, JSON, or other formats
• PEM structures and cryptographic material

Rather than flagging every suspicious string, the team applies AI-powered context-aware filtering to ensure only relevant and sensitive secrets are escalated. This reduces false positives and enables focused remediation efforts.

Step4: Validation & Classification

Not every secret poses the same level of risk. That is why each discovery is validated by assessing whether it is active, usable, and linked to critical systems.

Managed security service team answer key questions, such as:

• Is this secret in active use by any component or environment?
• Does it link to production or test systems?
• Could it allow unauthorized access or privilege escalation?

Once validated, secrets are categorized by type and severity. This structured classification helps teams prioritize what to fix first

By identifying and classifying these risks, Indusface helps organizations close gaps before they are exploited, enabling stronger, more secure code across all environments.

Finally, once secrets are identified and validated, Indusface provides guided remediation support. The managed security service team do not just send you a list of findings. They work closely with your dev and DevOps teams to recommend mitigation strategies.

Expert Recommendations to Prevent Secret Leaks

Based on recurring patterns observed during assessments, we recommend the following best practices to build long-term resilience against secret exposure. These insights are drawn from real-world cases and refined through years of hands-on experience across varied application stacks.

1. Never Embed Secrets in Public Code

Code served to browsers such as HTML and JavaScript is always accessible. Secrets such as API keys, access tokens, or signing keys must never be embedded in these assets. All sensitive operations should be routed through secure backend endpoints, where secrets remain protected and access controlled.

2. Use Environment Variables and Secret Managers

Avoid hardcoding sensitive data. Instead, rely on environment variables and modern secret management solutions like AWS Secrets Manager, Azure Key Vault, or HashiCorp Vault. This ensures secrets are securely stored, rotated, and accessed only by authorized services at runtime.

3. Isolate Environments Completely

Keep QA, staging, and production environments strictly separated. Use unique sets of credentials for each person. Reusing secrets across environments increases the risk of leaks. Also, test or staging environments should never be publicly accessible without proper access controls.

4. Regularly Rotate and Revoke Secrets

Secrets should never live indefinitely. Rotate them periodically and immediately revoke any that have been exposed or are no longer in use. Implement short-lived tokens and time-bound credentials wherever possible to minimize the impact of a potential leak.

5. Audit Code and Configuration Repositories Periodically

Old repositories and legacy code often contain hardcoded secrets that are forgotten but still active. Make regular audits a part of your security routine. Even unused branches or archived projects should be reviewed periodically.

6. Train Developers on Secure Coding Practices

Security is a shared responsibility. Equip developers with training to recognize and avoid unsafe practices such as:

• Hardcoding secrets in config files or scripts
• Pasting credentials into chat or shared docs
• Committing .env or .pem files to version control

A security-aware development culture reduces risk at the source.

7. Log and Monitor for Secret Misuse

Even with strong prevention, leaks may still occur. Set up monitoring on API endpoints, cloud accounts, and authentication systems. Track suspicious access patterns, failed logins, or unusual geolocation activity to detect and respond to potential misuse.

Securing Secrets Starts with Visibility

Exposed secrets can lead to serious breaches if left unchecked. Secret scanning helps you catch and fix these risks early. With Indusface’s expert-led approach, you gain the visibility and guidance needed to keep sensitive data out of your code and out of attackers’ hands.

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