Automated Identity Threat Detection in Construction

Construction firms operate across fragmented digital ecosystems - Procore project management, Autodesk Construction Cloud for design collaboration, Sage 300 for financials, Viewpoint Vista for field operations, and Primavera P6 for scheduling - each with independent user directories and access controls. When a subcontractor's credentials are compromised or a field superintendent's login is hijacked, IT teams have no unified visibility into which systems were accessed, what data was exfiltrated, or which job sites' sensitive bid documents, safety records, or AIA payment applications were exposed.

Manual identity audits across these platforms consume 40+ hours monthly and still miss lateral movement attacks that exploit cross-system trust relationships. The attack surface expands with every new trade partner, temporary worker, or consultant added mid-project.

Traditional identity and access management (IAM) tools treat Construction as generic enterprise, ignoring that a compromised estimator account can leak proprietary pricing models worth millions across multiple concurrent projects, or that unauthorized access to safety incident logs creates compliance violations under OSHA 29 CFR 1926. IT & Cybersecurity teams lack the operational context to distinguish between legitimate field access patterns and credential abuse until damage is already done.

Generic threat detection platforms don't understand that a superintendent accessing Bluebeam markup files at 2 a.m. from an unfamiliar IP might be normal (checking RFI responses from a different time zone) or malicious - requiring Construction-specific behavioral baselines to avoid alert fatigue that causes teams to ignore real threats.

Revenue Institute builds an AI identity threat detection engine purpose-built for Construction's multi-system environment. The platform ingests real-time authentication logs, API calls, and user behavior data from Procore, Autodesk Construction Cloud, Sage 300, Viewpoint Vista, Trimble, Bluebeam, and Primavera P6 through secure connectors, then applies deep-learning models trained on Construction-specific threat patterns - credential stuffing targeting estimators, lateral movement between project management and financial systems, data exfiltration of bid documents or safety records, and privilege escalation by subcontractor accounts.

The AI establishes behavioral baselines unique to each role: what a project manager's normal access pattern looks like versus what a field superintendent's looks like, accounting for time zones, mobile access from job sites, and seasonal staffing surges. When anomalies emerge - a field worker accessing Sage 300 payroll data, an architect's account querying multiple projects outside their scope, or bulk downloads of RFI documents - the system scores threat severity in real time.

For IT & Cybersecurity teams, this means moving from reactive incident response to proactive threat hunting. Automated actions quarantine suspicious sessions and trigger credential challenges without disrupting legitimate work; human security analysts review high-confidence threats with full context (which systems were accessed, what data was touched, how the pattern deviates from baseline) rather than chasing false positives.

The platform continuously learns from your Construction environment, refining models as new subcontractors onboard, projects scale up or down, and legitimate access patterns evolve. This is a systems-level fix because it unifies identity visibility across your entire tech stack - eliminating the blind spots where attackers hide between Procore and Sage 300, or between Bluebeam and Primavera P6.