Gurucul REVEAL

Analyzes identity telemetry (authentication events, access patterns, privilege use) in real time with behavioral baselines and risk scoring; leading implementations detect identity attacks in sub-second time.

Executes response actions against active identity attacks through playbooks with configurable automation: session revocation, credential reset, account isolation, inline step-up authentication or access denial at the identity provider, and follow-up policy and configuration hardening so the same attack cannot recur.

Detects named identity attack techniques with purpose-built detection content: password spraying, credential stuffing, pass-the-hash and pass-the-ticket, Kerberoasting, DCSync and DCShadow, golden and silver tickets, and consent phishing of OAuth applications, each mapped to MITRE ATT&CK so technique coverage can be verified against known identity attack scenarios. Complements Identity Behavioral Analytics (anomaly-based) and Identity Infrastructure Attack Detection (attacks on the IAM control plane).

Exchanges identity risk signals with identity providers, IGA, PAM, endpoint, and SIEM or SOAR platforms through bidirectional integrations and the Shared Signals Framework (CAEP, RISC), so a detection can revoke a session or force step-up in the identity provider within seconds and lands in the SOC as an enriched, correlated alert instead of a siloed one.

Detects credential-abuse techniques that defeat authentication controls, including MFA circumvention, session hijacking, and forged or replayed tokens.

Provides built-in orchestration and automated response through playbooks on alerts and cases rather than requiring a separate SOAR product.

Normalizes, enriches and risk-scores ingested data from third-party systems such as threat intelligence sources and CMDB.

Includes behavioral baselining and anomaly detection for users and entities in the core platform, eliminating the need for a separate UEBA product and the associated data movement.

Provides prebuilt reports and dashboards mapped to frameworks such as PCI DSS, HIPAA, and GDPR, with out-of-the-box breadth varying across platforms.

Ships vendor-maintained detection rules and use cases mapped to MITRE ATT&CK with minimal configuration, with breadth, accuracy, and update cadence varying across platforms.

Stores security event data long term with searchable recall across tiered hot and cold storage, with support for embedded or bring-your-own data lakes varying by platform.

Investigates, evidences and reports on security alerts with case management to support incident response.

Offers on-premises, cloud-hosted, cloud-native, and SaaS deployment options for data residency, sovereignty, and air-gap requirements, with availability varying by platform.

Filters, routes, transforms, and enriches event data in the ingestion pipeline before storage, letting teams drop low-value data and tier the rest to control volume and cost.

Queries event data in external stores, third-party data lakes, or other regions without first ingesting it into the SIEM repository.

Interoperates with XDR and extended telemetry and response sources such as EDR and NDR.

Manages and applies threat intelligence natively to enrich and prioritize detections, supporting vendor-curated and third-party feeds with availability varying by platform.

Automatically gathers and attaches context (threat intelligence, asset and identity data) to alerts during triage and investigation.

Performs initial triage of incoming alerts automatically, classifying and prioritizing them to cut tier-1 workload before a human touches the queue.

Lets analysts drive investigations and threat hunts through natural-language questions instead of query languages.

Identifies and dismisses false-positive alerts with documented rationale, reducing noise reaching human analysts.

Investigates alerts end-to-end from trigger to verdict and closes them out autonomously, so the full volume of raw alerts gets analyzed without resource-constraint concessions.

Recommends the next response actions to take based on investigation findings.

Generates investigation summaries and incident reports for analysts and leadership from completed investigation activity.

Aggregation, scoring, and operationalization of threat intelligence feeds to enrich alerts and drive automated response decisions.

Customizable playbooks that automate and orchestrate repeatable response tasks and multi-step workflows across security and IT tools.

Centralized case management to plan, track, and coordinate the response to security incidents, storing investigation data and evidence in one workspace.

Automatic enrichment and triage of incoming alerts to reduce manual analyst effort and prioritize genuine incidents.

Out-of-the-box connectors and APIs to security and IT systems that let playbooks read context and push enforcement actions.

Builds behavioral baselines per user account, device, and application, capturing access timing, resource usage patterns, and activity volumes specific to each entity rather than aggregate thresholds.

Combines multiple weak behavioral signals into a single risk score per user or entity, ranking which accounts warrant investigation so analysts focus on the highest-risk anomalies.

Models attacker-in-residence scenarios (pre-resignation data staging, after-hours privileged access, bulk download exceeding peer norms), with risk scores decaying appropriately for resolved anomalies.