Identity Fabric: How AI Enhances IAM & Modern Cybersecurity

The Core Disconnect in Modern Identity Management

A fundamental gap exists in how organizations approach cybersecurity. Teams typically manage identity and access management (IAM) in silos: IT operations focus on human identities, while DevOps or platform engineering teams handle non-human and machine identities. This disconnect is a primary vulnerability, evidenced by the fact that 80% of all cyberattacks today involve identity. The modern threat landscape has shifted; adversaries are no longer just “hacking in,” they are “logging in” using compromised credentials.

The solution is not to rip and replace existing infrastructure. Instead, the focus should be on creating an Identity Fabric. This concept involves augmenting the identity technologies you already have with AI-based capabilities to form a cohesive, integrated system that manages all identity types together.

The Fragmented Identity Landscape

Human Identities: A Complex Web

When organizations are asked about their strategy for managing human identities—both internal workforce users (WIAM) and external consumers/citizens (CIAM)—the answer is often just the name of a tool (e.g., Okta, Microsoft, Ping). This highlights a lack of a cohesive strategy. The reality is a complex environment composed of:

• Multiple Identity Providers (IDPs): Often a mix of old, homegrown systems, on-premise solutions, and modern cloud-based tools.
• Legacy Applications: Countless older applications that don’t support modern standards like multi-factor authentication (MFA), often relying on insecure methods like user ID/password side files or SQL tables.
• Hybrid Multi-cloud Environments: Managing workforce and consumer identities across various cloud platforms, each with its own native directories and tools, further complicates the problem.

Non-Human Identities: A Growing Challenge

The number of non-human identities often dwarfs that of human ones. These can be broken down into four main categories:

1. Machine Identity: The identity of an application or workflow.
2. API Keys: Credentials for programmatic access.
3. Public Key Infrastructure (PKI): Certificate-based identities (e.g., x509).
4. AI and AI Agents: A rapidly growing category where an AI agent has its own, often elevated, identity and must also act on behalf of the human user interacting with it.

This fragmented landscape makes enforcing universal security policies, such as least-privileged access, nearly impossible.

Six Critical IAM Use Cases

Organizations consistently struggle with a set of common challenges. The following six use cases represent the most pressing needs in modern IAM.

1. Identity Observability

Also known as Identity Security Posture Management (ISPM), this is the ability to find “sloppy” implementations that create vulnerabilities. It involves:

• Discovering hardcoded secrets in applications.
• Identifying shadow assets, such as unauthorized directories set up by departments.
• Crucially, observing the interaction between human and non-human identities. An example is seeing multiple human accounts, some of which have been inactive for years, suddenly begin using a single non-human service account—a clear indicator of a potential problem.

2. Frictionless Access

This focuses on improving user experience and security by moving away from traditional usernames and passwords towards technologies like passkeys. The goal is to make access seamless for the user while radically increasing security, but this is often hindered by legacy systems that don’t even support MFA.

3. Centralized Secrets Management

This is a foundational step for securing non-human identities. It involves establishing a central control plane to store, revoke, and audit secrets like API keys, database credentials, and cloud credentials. This provides visibility into who is accessing what, when, and how often.

4. Dynamic and Rotated Secrets

The next evolution beyond centralized static secrets is rotation and dynamic generation.

• Rotated Secrets: Regularly changing static credentials (e.g., every 30-60 days) builds the mechanisms required for immediate revocation if a secret is compromised.
• Dynamic Secrets: The ideal state where credentials are created just-in-time for a specific interaction and expire shortly after. This nearly eliminates the risk of leaked credentials, such as a developer accidentally committing a static key to a public GitHub repository.

5. Privileged Access Management (PAM)

Despite being a focus since regulations like Sarbanes-Oxley, most organizations have only implemented PAM controls for 20% to 70% of their privileged users, leaving a massive 30-80% unprotected. This gap is a major concern for auditors and cyber insurers, who are now demanding proof of 100% PAM coverage.

6. Identity Threat Detection and Response (ITDR)

ITDR moves threat detection from a general-purpose SOC tool closer to the identity engines themselves. Its primary function is to detect attacks on the identity system and, most importantly, identify policy bypasses. This includes detecting when a user accesses an application that requires MFA without any corresponding activity from the MFA engine, indicating a bypass.

A Three-Phase Strategy to Get Started

A pragmatic approach to building an Identity Fabric involves three phases:

1. Inspect: You can’t secure what you can’t see. This phase is about discovery and inventory.

   • Secret Identification: Find secrets wherever they live—in configuration files, code, wikis, and service tickets.
   • Identity Security Posture: Identify all shadow identities, directories, and assets to understand the full scope of the problem.

2. Protect: Implement the necessary controls to secure these discovered assets.

   • Implement centralized secrets management and PAM.
   • Deploy ITDR to find policy bypasses.
   • Use behavioral analysis to detect attacks leveraging compromised valid credentials. This is critical, as such attacks take an average of 292 days to identify and contain. Behavioral signals, like a user’s typing rate during authentication, can help detect a compromise in seconds.

3. Govern: Establish consistency across the entire identity lifecycle.

   • Implement and manage the full lifecycle for both human and non-human identities, including workflows for onboarding, offboarding, revocation, and denial.
   • Treat all identities with a consistent and secure management approach.

• Tags:
• AI Security
• Secrets Management
• Cybersecurity
• IAM
• Identity and Access Management
• Identity Fabric
• Zero Trust