Doppel

Continuously crawls dark web marketplaces, forums, and paste sites using automated web scrapers and AI-powered pattern matching to identify mentions of user credentials, email addresses, and personal identifiers. The system maintains indexed databases of known breach sources and applies machine learning classifiers to distinguish legitimate mentions from false positives, triggering real-time alerts when matches are detected against a user's monitored identity profile.

When a credential breach or identity threat is detected, the system generates contextual remediation steps tailored to the specific threat type and user's digital footprint. Using rule-based logic and threat intelligence databases, it produces actionable guidance (e.g., 'reset password on GitHub and linked services', 'monitor bank accounts for 30 days', 'file fraud alert with credit bureaus') rather than generic warnings, with links to relevant account reset pages and official resources.

Builds and maintains a comprehensive digital identity profile by accepting user inputs (email addresses, usernames, phone numbers, domain names) and cross-referencing them against known data breaches, public records, and dark web databases. The system continuously monitors this aggregated profile for new mentions, changes in exposure status, and emerging threats, maintaining a historical timeline of identity mentions and breach associations to detect patterns of targeted attacks.

Delivers threat alerts through multiple channels (email, SMS, push notifications, in-app) with configurable severity levels and delivery preferences. The system batches low-priority alerts to reduce notification fatigue while immediately escalating critical threats (e.g., credentials on active marketplaces) through all channels. Alerts include threat metadata (source URL, exposure type, affected accounts) and direct links to remediation guidance, with user-configurable quiet hours and alert frequency thresholds.

Maintains indexed databases of known data breaches, dark web paste sites, and credential marketplaces, with rapid query capabilities to match user identities against breach records. The system uses inverted indices and bloom filters for fast lookups across millions of breach records, with periodic updates from threat intelligence feeds and dark web crawlers. Queries return breach metadata (date, affected organization, exposure type, number of records) and associated threat context.

Presents aggregated threat data through a clean, non-technical dashboard with visual threat summaries, exposure timelines, and breach impact assessments. The dashboard uses color-coded severity indicators, charts showing exposure trends over time, and card-based layouts for quick threat comprehension. Reports can be generated in PDF format with executive summaries, detailed breach listings, and remediation recommendations, suitable for sharing with family members or business stakeholders.

Manages multiple subscription tiers with feature-level access control, determining which monitoring capabilities, alert channels, and reporting features are available to each user based on their subscription level. The system enforces feature gates at the API and UI level, with clear tier differentiation (e.g., basic monitoring vs. advanced dark web scanning, email alerts vs. multi-channel alerts). Tier upgrades/downgrades are processed with prorated billing and immediate feature access changes.