Frequently Asked Questions

AI Agents, Identity & Security Challenges

What unique identity and security challenges do AI agents introduce?

AI agents, especially agentic-AI, introduce challenges such as lack of human ownership, static permissions, shared secrets, and static credentials. These issues can lead to accountability gaps, data loss, non-repudiation risks, and incident remediation difficulties. The rapid adoption of AI agents often outpaces the maturity of identity and security controls, resulting in shadow-AI and poor visibility. (Source: Original Webpage)

Why can't agentic AI systems be managed like traditional web applications?

Agentic AI systems have unique characteristics, such as high volume, rapid growth, and complex credential rotation needs, which traditional human-centric identity models cannot handle. They often amplify existing identity and access management (IAM) shortcomings, such as poor MFA enrollment and excessive permissions. (Source: Original Webpage)

What are the main risks associated with static credentials and shared secrets for AI agents?

Static credentials and shared secrets increase the risk of unauthorized access, non-repudiation issues, and make incident remediation more difficult. Hardcoded or long-lived credentials are especially vulnerable to theft and misuse, amplifying risks in distributed AI environments. (Source: Original Webpage)

How does the 'Secret Zero Problem' affect AI agent security?

The 'Secret Zero Problem' refers to the challenge of securely authenticating AI agents without storing initial access credentials. Hardcoded secrets create vulnerabilities and increase breach risks. Addressing this problem is critical for secure, scalable AI agent deployments. (Source: Original Webpage, Knowledge Base)

What steps should organizations take to secure AI agent identities?

Organizations should discover and improve visibility of all actors in the AI ecosystem, identify and replace static or hardcoded credentials, assign owners to all accounts, migrate shared secrets to cryptographic credentials, and implement Just-in-Time (JiT) access models. Continuous verification and risk management are also essential. (Source: Original Webpage)

How can organizations improve accountability for AI agents?

Organizations can improve accountability by linking agentic identities to human owners, using unique naming, and ensuring traceability of agent events and transactions. Centralized identity provider models and cryptographic authentication help support end-to-end accountability. (Source: Original Webpage)

What is the role of cryptographic challenge-response in AI agent security?

Cryptographic challenge-response authentication replaces static credentials with short-lived, attested credentials, reducing the risk of credential theft and misuse. It supports federated access and enables scalable, secure identity management for AI agents. (Source: Original Webpage)

How does Akeyless help operationalize secure identity for AI agents?

Akeyless issues secretless, short-lived identities for AI agents and workloads, provides centralized visibility into identities and credentials, and enables discovery and replacement of hardcoded or long-lived secrets. It also supports continuous auditing and policy enforcement for agent access. (Source: Original Webpage)

What is the importance of Just-in-Time (JiT) access for AI agents?

Just-in-Time (JiT) access ensures that AI agents receive only the permissions they need, when they need them, minimizing standing privileges and reducing the risk of unauthorized access. JiT models are critical for enforcing the principle of least privilege in dynamic AI environments. (Source: Original Webpage)

How can organizations migrate from long-lived credentials to more secure alternatives for AI agents?

Organizations should identify and exchange long-lived credentials for short-lived, rotatable credentials, implement cryptographic challenge-response authentication, and use frameworks like SPIFFE for attestation and automatic credential issuance. (Source: Original Webpage)

Features & Capabilities

What are the core features of the Akeyless platform?

The Akeyless platform offers vaultless architecture, Universal Identity, Zero Trust Access, automated credential rotation, out-of-the-box integrations, a cloud-native SaaS model, and compliance with international standards like ISO 27001 and SOC. (Source: Knowledge Base)

Does Akeyless support secretless authentication for AI agents?

Yes, Akeyless enables secretless authentication for AI agents through Universal Identity, eliminating the need for hardcoded secrets and reducing breach risks. (Source: Knowledge Base)

How does Akeyless automate credential rotation for AI agents and workloads?

Akeyless automates credential rotation by providing features that replace static credentials with short-lived, rotatable secrets, reducing the risk of credential theft and ensuring credentials are always up-to-date. (Source: Knowledge Base)

What integrations does Akeyless offer for AI and DevOps workflows?

Akeyless offers integrations with Redis, Redshift, Snowflake, SAP HANA, TeamCity, Terraform, Steampipe, Splunk, Sumo Logic, Syslog, Venafi, Sectigo, ZeroSSL, ServiceNow, Slack, and SDKs for Ruby, Python, and Node.js. It also supports Kubernetes platforms like OpenShift and Rancher. (Source: Knowledge Base)

Does Akeyless provide an API for managing secrets and identities?

Yes, Akeyless provides a comprehensive API for its platform, with documentation available at docs.akeyless.io/docs. API Keys are supported for both human and machine identities. (Source: Knowledge Base)

What compliance certifications does Akeyless hold?

Akeyless is certified for ISO 27001, SOC, NIST FIPS 140-2 validation, PCI DSS, and is listed in the CSA STAR registry. These certifications demonstrate Akeyless's commitment to robust security and regulatory compliance. (Source: Original Webpage, Knowledge Base)

How does Akeyless support centralized visibility and control for AI agent identities?

Akeyless provides a unified identity control plane that centralizes visibility and management of human, machine, and AI agent identities across cloud and on-prem environments. This enables continuous auditing, policy enforcement, and risk analysis. (Source: Original Webpage, Knowledge Base)

What technical documentation and tutorials are available for Akeyless users?

Akeyless provides comprehensive technical documentation and step-by-step tutorials at docs.akeyless.io and tutorials.akeyless.io/docs to help users implement and use the platform effectively. (Source: Knowledge Base)

How does Akeyless help with credential lifecycle management for AI agents?

Akeyless manages the entire credential lifecycle for AI agents, including issuance, rotation, revocation, and verification, ensuring credentials are always secure and up-to-date. (Source: Original Webpage, Knowledge Base)

Use Cases & Benefits

Who can benefit from using Akeyless for AI agent identity security?

IT security professionals, DevOps engineers, compliance officers, and platform engineers in industries such as technology, finance, healthcare, manufacturing, and retail can benefit from Akeyless's solutions for AI agent identity security. (Source: Knowledge Base)

What business impact can organizations expect from using Akeyless?

Organizations can expect enhanced security, operational efficiency, cost savings (up to 70% in maintenance and provisioning time), scalability, improved compliance, and better collaboration between teams. (Source: Knowledge Base, Progress Case Study)

What pain points does Akeyless address for AI agent deployments?

Akeyless addresses the Secret Zero Problem, secrets sprawl, standing privileges, legacy secrets management challenges, high operational costs, and integration complexity, making AI agent deployments more secure and manageable. (Source: Knowledge Base)

Are there real-world examples of organizations using Akeyless for AI agent security?

Yes, organizations like Wix, Constant Contact, Cimpress, and Progress have successfully implemented Akeyless for centralized secrets management, Universal Identity, and Zero Trust Access, achieving enhanced security and operational efficiency. (Source: Knowledge Base, Case Studies)

What industries are represented in Akeyless's customer base?

Akeyless serves customers in technology (Wix, Dropbox), marketing and communications (Constant Contact), manufacturing (Cimpress), software development (Progress Chef), banking and finance (Hamburg Commercial Bank), healthcare (K Health), and retail (TVH). (Source: Knowledge Base)

How quickly can organizations implement Akeyless for AI agent identity security?

Akeyless's cloud-native SaaS platform allows for deployment in just a few days, with minimal technical expertise required and comprehensive onboarding resources available. (Source: Knowledge Base)

What feedback have customers given about the ease of use of Akeyless?

Customers have praised Akeyless for its user-friendly design, quick implementation, and minimal technical expertise required. Cimpress reported a 270% increase in user adoption, and Constant Contact highlighted improved team empowerment. (Source: Knowledge Base, Case Studies)

How does Akeyless improve operational efficiency for AI agent management?

Akeyless centralizes secrets management, automates credential rotation, and streamlines workflows, saving up to 70% in maintenance and provisioning time, as demonstrated by Progress. (Source: Knowledge Base, Progress Case Study)

Competition & Comparison

How does Akeyless compare to HashiCorp Vault for AI agent identity security?

Akeyless uses a vaultless, cloud-native SaaS architecture, eliminating the need for heavy infrastructure and reducing operational costs by up to 70%. It offers Universal Identity and automated credential rotation, making it faster to deploy and easier to manage than HashiCorp Vault. (Source: Knowledge Base)

What are the advantages of Akeyless over AWS Secrets Manager for AI agent deployments?

Akeyless supports hybrid and multi-cloud environments, offers better integration across diverse platforms, and provides advanced features like automated secrets rotation and Zero Trust Access, making it more flexible and comprehensive than AWS Secrets Manager. (Source: Knowledge Base)

How does Akeyless differ from CyberArk Conjur for AI agent identity management?

Akeyless unifies secrets, access, certificates, and keys into a single SaaS platform, reducing the need for multiple tools and simplifying operations. Its cloud-native architecture supports scalability and seamless integration with DevOps tools. (Source: Knowledge Base)

What makes Akeyless a preferred choice for AI agent identity security?

Akeyless stands out due to its vaultless architecture, Universal Identity, Zero Trust Access, automated credential rotation, cloud-native SaaS model, and robust compliance certifications. These features address critical pain points and provide a scalable, cost-effective solution for AI agent identity security. (Source: Knowledge Base)

Who are some notable customers using Akeyless?

Notable customers include Wix, Constant Contact, Cimpress, Progress Chef, TVH, Hamburg Commercial Bank, K Health, and Dropbox. (Source: Knowledge Base)

Technical Requirements & Support

What technical resources are available to help with Akeyless implementation?

Akeyless provides platform demos, self-guided product tours, tutorials, technical documentation, 24/7 support, and a Slack support channel to assist with implementation and troubleshooting. (Source: Knowledge Base)

How easy is it to get started with Akeyless for AI agent identity security?

Getting started is easy with Akeyless's intuitive interface, pre-configured workflows, and comprehensive onboarding resources. Users can schedule demos, start a free trial, or take a self-guided product tour. (Source: Knowledge Base)

Does Akeyless support hybrid and multi-cloud environments for AI agent identity management?

Yes, Akeyless is designed as a cloud-native SaaS platform that supports hybrid and multi-cloud environments, providing flexibility and scalability for organizations of all sizes. (Source: Knowledge Base)

Where can I find more information about Akeyless's AI agent identity security solutions?

For more information, visit the Akeyless blog, technical documentation, tutorials, and case studies, or contact Akeyless directly for a demo or expert consultation. (Source: Original Webpage, Knowledge Base)

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From Anonymous to Accountable: Giving AI Agents a Digital Identity

Rise of Agents & Why They’re Different

  • Increase and Benefits of Use
  • Complex Characteristics NHI Volume, Human Behaviour

AI-driven automation has accelerated rapidly over the past year, delivering unprecedented productivity and business agility across industries and sectors. The benefits are both broad and considerable. Nearly all areas – across both the public and private sectors are experiencing increased adoption of agentic-AI capabilities. 

However this has brought some considerable identity and security challenges from an operational perspective. The innovative speed of AI and agentic deployments has been rapid – whilst identity and security components are often being left behind – resulting in the poor selection of controls or the avoidance of controls entirely. Shadow-AI is likely to be considerable in many organisations as non-technical decision makers experiment with online SaaS delivered models and chatops interfaces. But why is this an issue? Why can’t agentic systems simply be managed like any other web application?

Well they exhibit a new and somewhat unique set of characteristics. If we take a brief step back and understand that identity models typically cover three-main sub-categories: identity for software, hardware and people. The people-centric area is the most mature from a technology and framework perspective, namely as that is where many commercial identity and access management (IAM) features were designed for. Workforce B2E (business to employee) single sign on (SSO), access review and then later in the early 2000s life cycle management – driven by compliance and productivity challenges. 

The last decade has seen the dedicated emergence of service, workload and non-human identity (NHI) tools and concepts too. NHIs have created non-functional requirements that existing human identity models cannot cope with (think volume, growth and credential rotation capacity) and create some interesting challenges themselves. For example how to replicate the assurance associated with biometric authentication to workloads? 

Whilst the organizational maturity for human identity may be higher than for NHIs, organisations are still plagued with numerous human-centric IAM challenges – such as poor MFA enrolment, excessive permissions, poorly executed access review and slow cleanup operations.

To that end we start to see agentic-AI being somewhat shoe-horned between being non-human in nature, but heavily reliant on human interactions and patterns of access on the other – and often amplify the failings in deployment in both camps.

Problems With Existing Identity & Cyber Security Models

  • How to Apply Strong Auth to Agents?
  • Migrating from Long Lived Credentials
  • Secretless AI Agents: Enabling Identity Without Secrets

We can then start to see the amplification of issues in both the human and non-human identity worlds. Excessive permissions for humans coupled with a lack of visibility for non-human identities. A lack of authoritative source for workloads, but the rapid creation and management of agentic-AI. This is creating a cascading set of access control, visibility and behaviour management problems that existing tools and models of security were not designed to cope with.

For example, from a people-centric identity point of view the concept of strong authentication is well understood. The implementation of strong authentication or MFA is still not quite complete however – and many internal and external systems still rely on shared secrets and passwords. Why? Integration complexity, service consolidation, end user behaviours and cost act as barriers to adoption – even though concepts like cryptographic challenge response and initiatives like FIDO have effectively solved the technical problem.

ActorFactorRisk
Agentic-AILack of Human OwnerAccountability
Agentic-AIStatic PermissionsData Loss
Agentic-AIShared SecretsNon Repudiation
Agentic-AIStatic CredentialsIncident Remediation

The same concept can then be applied to excessive permissions, a lack of just in time access request enforcement or the removal of ghost accounts. Many security design points that are well understood but are often not entirely implemented.

So we need to ground our analysis not just on what is needed to manage and secure the agentic world, but to also consider that the foundations for agentic security are potentially sitting on top of poor human-centric identity and access management maturity or implementation.

A cascading set of issues start to emerge, from not being able to link an agentic identity to a carbon-life form, to perhaps linking to a human identity that should actually be disabled or removed, has excessive permissions or shouldn’t even have access to the agent in the first place.

If we take some concepts from the human world that are mature in design – concepts like strong authentication, a movement away from shared secrets and centralised visibility and control – how can those concepts be adapted and implemented for the agentic-world?

A common design flaw for NHI implementations has often been the use of both shared secrets and a long-lived nature of those credentials – too often hard-coded into API-clients or reusable code blocks. Translating those poor practices into the agentic world sees a huge amplification on the impact and likelihood for both internal and external adversarial activity.

What are the alternatives? Firstly humans are migrating from a shared-secrets model (i.e. passwords and PINS) to cryptographic challenge-response concepts – why not NHI and agentic? The identification of static string-based credentials that are hard-coded and difficult to rotate should be part of any risk discovery process with the continual scanning of existing code repositories. The next stage is a migration to something more secure, scalable and short-lived.

Cryptographic Foundation and Secretless

  • Improving Accountability & Repudiation
  • Credential Life Cycle Management for Agents

We need to understand that credential management is a life cycle and operates within a broader ecosystem. That life cycle includes issuance and usage, but also rotation, revocation and an initial verification process – often known as the secret-zero problem. Unlike human-centric approaches to authentication where both biometric and an interactive set of stages can be utilized, the issuance (of public/private key pairs for challenge response) credentials still requires an initial verification of the NHI or agentic-identity that is requesting association to the credential. 

Concepts like SPIFFE (secure production identity framework for everyone) can help here – by providing an interoperable model for processes to be attested independently during that initial credential creation and association phase – essentially making sure the correct thing gets the correct credential at the correct time.

Of course in the NHI and agentic worlds this needs to happen automatically and at scale. Then what? Well the credentials that are minted and issued – albeit likely to support strong authentication – also need to have some additional characteristics. They should be short-lived and ephemeral – either automatically expiring after a set time or task completion – or auto-rotatable – supporting an entirely repeatable and programmatic way to generate new credentials – reducing blast radius impact of credential theft and misuse.

Whilst subtly different, how the credentials are used and scoped should also be considered. By this we need to gain an understanding of what the credential is being used for. What happens post authentication with respect to authorization, access control and enforcement? This should include concepts such as the principle of least privilege – assigning permissions only when needed of course, but also only assigning permissions that are needed to complete the objective that has been set.

The Road Ahead

  • Discovery, Visibility and Risk Analysis
  • Unified Identity Control Plane for Humans, Machines, and AI Agents

It is important to consider what can be controlled from an agentic-AI perspective. Whilst human-related risk exists and will continue to do so, understanding and then prioritizing countermeasures for agents is critical. But where does the immediate risk exist? 

RiskActionGoal
Hardcoded SecretsCode scan for hard coded strings, secrets, keysMove to cryptographic challenge response authentication
Long lived CredentialsIdentify and exchangeShort lived and rotatable credentials
Hard coded bootstrappingMigration to SPIFFEAttestable processes and automatic issuance of creds
Distributed authenticationMigration to federated accessCentralised identity provider function for NHI/Agentic

NHI and agentic systems are plagued with being built in a distributed and often isolated manner – resulting in an isolated and inconsistent approach to authentication and credential management. The strategic aim is to deliver a centralized identity provider model, with modern challenge response authentication that can in turn be used for downstream access control enforcement. The use of shared secrets, long lived certificates and hard-coded keys is common and should be identified for both existing deployments and new services.

The use of a cryptographic based authentication capability that can support federated access also helps deliver a more accountable identity function for agents and workloads. Unique naming, and an ability to link back to a carbon-life form helps support the end to end traceability of agent events and transactions – even if the resources being accessed are across business or operational boundaries.

The rise and complexity of agentic-AI will continue throughout 2026. It is becoming a critical capability for organisations relying on such systems to understand the key authentication challenges this can bring as an immediate priority. More strategic approaches to just in time access and dynamic permissioning can only be built if a scalable and ephemeral identity provider model is in place.

Getting Started

The identity and security management of the entire AI ecosystem requires both a strategic operational understanding, but also an end to end view of the identities, accounts and credentials engaging with it.

FirstNextIterate
  • Discover and improve visibility of actors engaging with AI ecosystem
  • Identify static, hard coded and long live credentials within code and services
  • Identify standing and excessive permissions associated with agents/services
  • Develop a high level AI vulnerability risk management function
  • Look to assign owners to all accounts and identities within the AI landscape
  • Look to migrate all shared secrets to cryptographic credentials
  • Look to migrate static credentials to rotatable ones
  • Look to migrate static permissions to a JiT model
  • Continually verify associated and used permissions
  • Continually verify identities and accounts accessing AI data sources
  • Discover new applications, services, MCP servers

Put Principles Into Action with Akeyless

Akeyless helps organizations operationalize these recommendations by issuing secretless, short-lived identities for AI agents and workloads and providing centralized visibility into identities and credentials across cloud and on-prem environments. Teams can discover hard-coded or long-lived secrets, replace static credentials with rotatable or Just-In-Time access, and continuously audit which agents access which resources under defined policies.

About The Author

Simon Moffatt has over 25 years experience in IAM, cyber and identity security. He is founder of The Cyber Hut – a specialist research and advisory firm based out of the UK. He is author of CIAM Design Fundamentals and IAM at 2035: A Future Guide to Identity Security. He is a Fellow of the Chartered Institute of Information Security, a regular keynote speaker and a strategic advisor to entities in the public and private sectors.

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