AI | Machine IAM | Security

The Myth of the Solved Secret: Why Credentials Are AI’s Most Dangerous Vulnerability

Summary AI security discussions often focus on prompt injection, model vulnerabilities, and patching. But one of the most immediate risks is much more familiar: compromised credentials. AI agents require credentials to access enterprise systems and can also discover credentials exposed elsewhere. Because agents operate at machine speed and scale, even short-lived credentials can provide enough […]

AI | Security

EU AI Act Compliance: Mapping Identity Security Controls

The European Union’s AI Act is the world’s first comprehensive legal framework for artificial intelligence. It takes a risk-based approach, applying stricter obligations to AI systems that could significantly affect people’s safety or fundamental rights. The regulation entered into force on August 1, 2024, with requirements phased in over time. Some provisions are already enforceable, […]

AI | Machine IAM | Security

The Limits of Vaulting AI Agent Credentials

Quick Answer: Palo Alto Networks Unit 42 showed how a prompt-injected AWS AgentCore agent could steal and replay a credential even though it was securely stored in AgentCore Identity. The research exposes a broader problem with AI agent security: protecting credentials at rest and in transit is not enough if they become readable inside the […]

Security

47-Day Certificates: What Changes and How to Prepare

Learn when 47-day certificates take effect and how automated certificate lifecycle management can reduce renewal and outage risk.

Security

How to Eliminate Static Secrets with Identity-Based Access

Learn how to replace static secrets with dynamic credentials, workload identity, and Zero Standing Privileges using a practical phased approach.

AI | Machine IAM | Security

Gartner on Machine IAM: Govern the Identity, Not the Credential

Quick Answer: Machine IAM shifts security from managing credentials as standalone objects to governing the identities of workloads and AI agents directly. That means establishing who or what is requesting access, issuing short-lived authority based on policy, and maintaining ownership and lifecycle context as those identities change. For autonomous agents, that model increasingly extends into runtime, […]

Security

Embracing a Secretless Approach with Akeyless

Key Takeaways Answer Capsule: What Is Secretless Authentication? Secretless authentication is an approach that lets machines, services, and applications authenticate to systems and each other without ever holding a static, storable secret, such as a hardcoded API key or a long-lived certificate. Instead, a workload proves its identity (through a cloud IAM role, a Kubernetes […]

Platform Engineering | Security

The Complete Guide to Multi-Vault Secrets Governance

Multi-vault secrets governance gives enterprises a consistent way to control access, rotation, and audit activity across existing secrets managers. Because those secrets can remain in AWS Secrets Manager, Azure Key Vault, Google Secret Manager, Kubernetes, or HashiCorp Vault, security teams gain clearer visibility without first moving everything into a new store.

AI | Platform Engineering | Security

How to Secure Credentials in AI Agents

To secure credentials in AI agents, start by giving each agent a unique identity for the task. Limit access to only the systems and actions required, make that access short-lived, and apply intent-based access controls at runtime. Keep credentials and policy enforcement outside the agent, then revoke access as soon as the task is complete.

AI | Security

Anthropic’s Latest Threat Report Shows How AI Is Industrializing Secret Theft

Quick Answer: Anthropic’s September 2026 Threat Intelligence Report shows how AI is compressing the path from exposed credential to enterprise compromise. One suspected ShinyHunters affiliate scanned 1.8 million Android apps for hardcoded secrets, while related operators used AI to accelerate reconnaissance, token abuse, data collection, and exfiltration. For defenders, faster secret scanning is only part […]

Platform Engineering | Security

Why Secrets Sprawl Grows in Large Enterprises

Secrets sprawl grows when enterprises add applications and access requirements without consistently updating how credentials are distributed and retired. Acquisitions introduce separate secrets stores, while deployment workflows create additional copies of credentials. As ownership and access policies diverge, security teams struggle to determine which credentials remain necessary and how to revoke them safely.

Platform Engineering | Security

Why Enterprise Secrets Management Fails at Scale

Secrets management at large enterprises often breaks down when teams have to manage a growing number of credentials across systems with different access policies and rotation processes. As applications spread across cloud and on-premises environments, keeping those controls consistent takes more manual effort, and no single team has a complete view of what needs attention. Rotation gets postponed because application dependencies are unclear, while developers waiting on access find their own ways to keep deployments moving.