Speakers
Synopsis
In the current era of rapid AI advancement, the continuous emergence of new AI tools every week underscores the significance of evaluating their impact on organizations responsible for managing their bots, RPAs, and machine identity access.
- 93% of organizations had two or more identity-related breaches in the past year.
- Machine identities are identified as the primary cause of identity growth and are perceived as the riskiest type of identity.
- 50% of organizations expect identities to grow 3x in the next 12 months.
Zero trust strategies have traditionally emphasized the management of user identity and integrated identity-based authenticators to authenticate humans. However, in this approach, we may have unintentionally neglected the many silent, autonomous machines that are present both within and outside our perimeters. The potential ramifications of machines being compromised and infiltrated with a trojan include unauthorized access to sensitive data, disruption of operations, and potential damage to the organization's reputation.
Zero Trust Architectures can be tailored to support machine identity management through the implementation of robust authentication and authorization mechanisms specifically tailored for machines. It is essential to guarantee that the correct entities, whether individuals or machines, have timely and appropriate access to the necessary resources for the right duration and reasons.
Machine identities include devices, digital workloads, workload identities, and robotic process automation (RPA) bots. They are utilized by entities that are unable to modify passwords or enable multi-factor authentication like biometrics. Typically, machine identities have lengthy passwords that do not have an expiration date. To safeguard these credentials, numerous organizations enforce policies to regularly rotate or change the password. Nevertheless, this presents a challenge if the machine identity is integrated into an application or utilized by a tool, as changing its password may disrupt the dependency that the application or tool relies on.
These digital identities for machines can utilize symmetric or asymmetric cryptographic keys, tokens, or passkeys.
Machine identities, unlike human identities, can emerge from any part of an organization. Insecure coding practices can lead to the presence of backdoor machine identities, including hard-coded credentials within an application, service, or script, whether they are intentionally created or unintentionally left behind.
Furthermore, legacy machine identities can present a substantial challenge for organizations. They may lack documentation, utilize vulnerable cryptographic algorithms or outdated security controls, and have uncertain ownership.
Implementing a Formal Process for Managing Machine Identities:
1. Establish Ownership and Accountability
2. Define Clear Relationship Between Identity and Role Grants
3. Treat Machine Identities Like Human Identities
- Implement least privilege and Just-in-Time (JIT) Access.
4. Centralize and Secure Digital Certificates, SSH Keys, and Secrets
- Store in Hardware Security Modules (HSM) or key vaults.
5. Move to an Identity-Centric Approach
- Utilize common tools like gateways, encryption, or key management.
6. Ensure Continuous Monitoring and Auditing
- Use anomaly detection for abnormal activities.
7. Periodically Detect Compromised Machine Identities
- Disable or deactivate them.
8. Incorporate Machine Identity Management into Overall Security and Risk Management
9. Identify and Document Machine Identity-Related Outages
