Specialized ML-driven data-centric classification designed to protect secrets and reduce risk
BigID, the leading platform for data security, compliance, privacy, and governance, today introduced purpose-built AI and ML-based data discovery and classification capabilities designed to quickly and easily detect secrets across enterprise data and reduce risk from potential data breaches and leaks.
Secrets – including as API keys, tokens, usernames and passwords, and security certificates – are commonly shared, cloned, and distributed across enterprise data environments as a means for better collaboration and efficiency. Unfortunately, the proliferation of secrets across these environments increases the attack surface and quickly raises security risks. Data containing secrets can inadvertently get pushed into production, while other secrets can be exposed to internal and external bad actors.
With BigID’s native secrets detection capabilities, organizations can:
- Scan for secrets across the entire software development ecosystem including GitLab, GitHub, Jira, Confluence, Powershell scripts, Slack, and hundreds of other data sources across the environment
- Detect secrets faster and more accurately using patented AI and ML-based data classification techniques
- Proactively protect secrets with streamlined and automated remediation to continually mitigate the threat of exposure
“Secrets-in-code remains one of the most overlooked vulnerabilities in security, despite being a priority target in some of the biggest breaches of late,” said Tyler Young, CISO at BigID. “BigID’s purpose-built AI and ML-based data discovery and classification give security teams speed and confidence to protect secrets from unwanted exposure so they don’t become another headline.”
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