Identity Security positions digital identity—its lifecycle, authentication, and authorization—as a core pillar of cybersecurity. Many prominent attack types converge on the same prerequisite: gaining access to highly privileged accounts that unlock sensitive data and downstream systems. Across advanced persistent attacks on critical infrastructure, malicious insiders, and software supply chain attacks, privileged identities and their access paths repeatedly serve as the leverage point to reach critical resources.
Traditional IAM approaches focus on lifecycle management, recertifying static entitlements, strengthening authentication (including contextual risk), and privileged access controls. Yet access governance remains heavily role-based and manually complex, especially when layered entitlement models exist in major systems. This makes it difficult to maintain clear visibility into who has which access. More importantly, static entitlements show only “the tip of the iceberg”; behavioral outliers—how entitlements are actually used—are more relevant for detecting identity-driven threats. The rise of dynamic cloud workloads and non-human (“silicon”) accounts further reduces the effectiveness of static control methods.
Sharelock addresses this gap with an Identity Threat Detection & Response (ITDR) and Cloud Workload Protection (CWPP) solution that augments existing IAM and SOC tooling. It ingests both static entitlement data and dynamic activity data (including IAM audit trails and concrete user actions) from IAM systems and business applications, normalizes and correlates it, and models “habits” to flag anomalies. Anomalies are then evaluated to determine which are real threats versus legitimate, non-routine activity. The platform supports response actions and integrates with SIEM/SOAR. It offers an ITDR reference model with 50+ Indicators of Behavior (IoBs), an unsupervised, rule-less ML approach, flexible baselining, and dashboards that highlight risky entities/users, “should-be vs as-is” gaps, and early threat signals. Key challenges include expanding integrations, playbooks beyond SAP, and growing its partner ecosystem.
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