Most secret detection tools focus on known patterns. They analyze code for standardized formats like AWS keys, GitHub tokens, or Twilio credentials. However, over 50% of secrets do not follow standardized formats. Generic secrets like custom API keys, internal authentication tokens, database credentials, and encryption keys often follow organization-specific or random formats.
Tools that only look for known patterns fail to detect these generic secrets leaving a dangerous gap. An effective secrets solution needs to identify generic secrets without creating too much noise and deliver across four core capabilities:
- Detection of all secrets–including generic secrets–to avoid risky false negatives
- Precision to reduce false positives and noise
- Coverage to detect secrets across the entire SDLC
- Customization to allow custom rules to improve generic secrets detection and accuracy
Cycode’s industry-leading Secrets Engine detects standardized and generic secrets with high precision across the entire SDLC with enterprise-ready customization.
Detect More Than Just Common Secrets
Traditional solutions rely on predefined regex patterns to detect secrets. While this works for common secrets, it fails to catch custom, undocumented, or organization-specific credentials. With over half of the secrets falling under the generic secret umbrella, Regex-based tools leave wide gaps with critical credentials going undetected.
Consider this example: A custom API key X9#kN2!V@ has been hard-coded into an application. The secret does not resemble a known or standard pattern; however, it is a critical credential. A traditional regex-based scanner analyzes the code but fails to flag the hardcoded secret because it does not follow a standardized format. The undetected secret persists and introduces risk.
Unlike a regex-based scanner, Cycode’s Generic Secrets Detection identifies secrets based on more than pattern recognition. Cycode analyzes entropy, structure, and context to flag secrets that consist of unknown or custom patterns. By measuring the entropy or randomness of strings in code, Cycode can flag those that are suspiciously random as potential secrets, even if they do not match known patterns. Cycode also analyzes the code around the secret to understand the type of secret based on context. In the scenario above, Cycode will detect the secret and ensure the critical credential does not go undetected and unsecured.
Reduce False Positives & False Negatives with AI-Powered Precision
Precision matters in generic secrets detection. On one hand, teams struggle with too many false negatives when traditional scanners miss high-risk custom secrets that do not fit predefined patterns. On the other hand, simple regex-based tools often misclassify random strings as secrets generating high numbers of false positives and overwhelming security teams. .
Cycode delivers precise feedback by leveraging machine learning (ML) and heuristics to identify generic secrets and analyze detected issues to determine if a secret is real. Using our ML model, customers achieved:
- 70% reduction in false negatives – so critical secrets don’t slip through the cracks.
- 80% reduction in false positives – so security teams get fewer noisy alerts.
This means faster, more accurate secret detection with significantly less manual effort.
Secure the Entire SDLC & Beyond
Many security tools are limited to source code scanning or a limited set of integrations. However, secret sprawl and exposure extend beyond source code and SCMs. Cycode detects generic secrets across the entire SDLC pipeline and ecosystem. This includes integrations with Container, Cloud, and CI/CD tools like Docker Hub, Kubernetes, Jenkins, and more, as well as integration with productivity tools like Jira, Confluence, Slack, Microsoft Teams, and SharePoint. This ensures complete coverage where exposure happens.
Customize Rules for Your Enterprise with Cycode’s AI Regex Builder
Most organizations—especially large enterprises—have unique authentication mechanisms and internal secrets. Traditional tools don’t account for these custom keys.Cycode addresses this gap with its AI-powered Regex Builder, a feature designed to help security teams create custom rules without needing deep expertise in regular expressions. Writing accurate regex patterns can be notoriously tricky, but Cycode simplifies the process by leveraging AI to generate precise, effective patterns.
With this capability, internal secrets are detected just as effectively as standard credentials, ensuring stronger, more comprehensive protection even for organization-specific secrets that other tools can’t identify.
Secure All Your Secrets with Cycode
Cycode’s secrets detection solution empowers you to identify and secure all secrets across your enterprise SDLC. Unlike regex-based detection and limited tools that detect some secrets in some environments with middling accuracy, Cycode’s precise, holistic, and AI-driven approach equips you to reduce risk from hardcoded and exposed secrets with:
- Broad Coverage for Known and Generic Secrets – Detects secrets competitors miss, including unknown and custom secrets.
- High-Precision Accuracy – AI-powered detection significantly reduces false positives and captures more real secrets.
- Full SDLC Detection – Holistic scanning across SDLC pipeline and productivity tools.
- Enterprise Adaptability – Supports custom rules and Cycode’s AI Regex Builder to fit an organization’s unique security needs.
- Full Lifecycle Management – Seamless detection, remediation, and workflow automation for faster response.
Get a demo to learn more about Cycode’s Secrets Security & Detection solution.
