The rapid proliferation of AI agents accessing sensitive systems is driving demand for new security protocols, with organizations increasingly focused on preventing the exposure of credentials used by these autonomous systems. According to security experts, traditional methods of secret management, such as storing API keys in environment variables, are proving inadequate for the dynamic and often ephemeral nature of agentic AI.
In 2024, GitGuardian reported 23,770,171 newly discovered hardcoded secrets in public GitHub repositories, a significant increase from the previous year. The risk is even greater for private repositories, where 35% contain such exposed credentials. This poses a substantial threat, as compromised keys can allow attackers to drain LLM credits, access sensitive data, or penetrate internal networks.
Several companies are now offering specialized secret management tools designed to address the unique challenges posed by AI agents. Doppler, described as a “Universal Secrets Manager,” is gaining traction among AI startups due to its ease of use. Other platforms, including Vault, Infisical, and CyberArk Secure AI Agents, are also vying for market share. CyberArk emphasizes the need for “industry-first privilege controls” for AI agents, focusing on discovery, management, and secure access with a “zero standing privileges” approach.
A key requirement for these tools is the ability to handle dynamic secrets – credentials that are automatically generated and rotated – and to work seamlessly with agent frameworks like LangChain, AutoGPT, and CrewAI. The need for short-lived credentials tied to an agent’s identity and task context is becoming increasingly critical, as static secrets are vulnerable in rapidly evolving workflows. According to a report from Security Boulevard, access decisions must be made in real time as AI agents assemble and execute pipelines on the fly.
The rise of “non-human identities” – machine identities – is outpacing the capabilities of existing security systems. Compliance frameworks like SOC 2, ISO 27001, and FedRAMP are also raising the stakes, demanding more robust secrets management practices. Doppler highlighted this challenge in a 2025 report, noting that the cost of inaction is both risky, and expensive.
CyberArk’s Secure AI Agents solution focuses on discovering AI agents across various environments – SaaS, cloud, and developer environments – and enriching them with contextual information such as ownership, purpose, and permissions. The company’s AI Agent Gateway acts as an enforcement point, granting permissions only for specific tasks and automatically revoking them afterward. The platform also provides visibility and auditability into agent actions and communications.
The industry is responding to the need for solutions that can handle the scale and oversight required to onboard, manage, and deprovision the growing number of AI agent identities. Fast.io offers workspaces and collaboration tools specifically designed for AI development, emphasizing secure secret management as a core component.
