CypherEye verifies that the “right human” is live and present behind every transaction

Human Factor Authentication (HFA) is CypherEye’s multimodal, continuous, and passive approach to identity verification. Rather than relying solely on a point-in-time login, credentials, or device tokens, HFA continuously evaluates whether the authorized human is behind an ongoing transaction in real time using signals derived from human biology, behavior, and environment. Together, these signals create what CypherEye calls a “Unique Digital DNA,” which feeds an AI-generated Trust Score that is continuously updated.

Growing evidence shows that today’s standard biometric methods—commonly used to unlock devices and confirm transactions—can be spoofed, particularly as deepfakes and agentic AI become more sophisticated. CypherEye’s Human Factor Authentication (HFA) focuses on real human trust through a realtime Trust Score. Because the score is derived from multiple signals rather than a single biometric input, it is significantly more difficult to replicate through a single spoofing technique. HFA complements existing authentication methods by adding another layer of security and increasing confidence that the authorized human is actually behind the transaction.

No. CypherEye is designed to reduce authentication friction. It operates passively in the background and continuously strengthens the user’s identity model through interactions with the smartphone. Unlike active methods such as Face ID, fingerprint scans, or one-time passcodes, CypherEye requires no deliberate action during normal use and authentication becomes more seamless as the system continuously evaluates whether the authorized human is behind the transaction.

CypherEye is complementary to passkeys and hardware-based authentication, not a replacement for them. It adds a continuous, passive Trust Score after the initial authentication event, helping detect account takeover or session hijacking that can occur after a valid passkey or hardware-based login. CypherEye also provides an additional dimension of assurance by evaluating whether an authorized human—not simply a device, credential, or automated system—is actually conducting the transaction.

Many existing solutions derive risk or trust scores from shared or aggregated transactional behavior across services. CypherEye takes a different approach by generating its Trust Score at the source while keeping underlying data private rather than pooling it across services. This makes CypherEye complementary to existing authentication and fraud-prevention platforms.

The Trust Score is a real-time score from 0 to 100 that reflects CypherEye’s level of confidence that the authorized human is present and participating in a transaction. It is generated by CypherEye’s AI models and statistical engine using smartphone sensor data and is continuously updated in the background without interrupting the user experience.

CypherEye derives trust from multiple passive signals—such as gait, micro-vibrations, voice, and— rather than relying on any single biometric. If one signal becomes less reliable, the system can re-weight the remaining signals rather than allowing the degradation of one input to undermine authentication. User baselines are continuously recalibrated, allowing gradual changes, such as injury recovery or environmental shifts, to be incorporated without triggering false negatives.

A custom Hardware Abstraction Layer provides a consistent interface across diverse platforms.

CypherEye is designed to support GDPR and CCPA compliance requirements, with data processed and stored privately on the device rather than pooled or shared across services. User consent is required before data collection begins, and the data is not legible or sold or shared.

The CypherEye technology is linked into the customer’s application so is protected inside the execution space. The Trust Score data is transmitted through an encrypted, secure channel between the CypherEye application and CypherEye servers, with end-to-end protection. Because the score is continuously derived from a combination of biological, behavioral, and environmental signals rather than a single input, an attacker would need to convincingly replicate multiple signals simultaneously and sustain that replication throughout an ongoing session. Anomalies in individual signals can affect the Trust Score in real time, making a static, one-time spoof significantly less effective.

CypherEye’s ID capture feature allows the user to scan any issued physical identity card and match it to it's facial recognition capability. In addition, An open framework canintegrate with any global Identity. Verification Service. Each user has a singular and unique identifier (CypherID) which can be connected to emails and multiple user smart phones and, further to authorized non smart phone devices.

CypherEye onboarding is designed to be comparable to enrolling in a conventional biometric system, such as Face ID or fingerprint recognition. After the initial setup a cross-training of the human authentication models, operate passively in the background, providing additional security with minimal ongoing effort from the user. An AI based tutorial on the app, allows the user to improve their scores and create a more accurate “unique digital DNA”.

Yes. Because sensors and device specifications can vary, each smartphone must be trained separately. Each device generates its own Trust Score, providing the assurance associated with that specific device and its relationship to the authenticated user.

CypherEye currently generates the Trust Score on smartphones. That Trust Score can then be used to help authenticate the user on other devices, including computers and tablets.

CypherEye’s behavioral analytics operate continuously. As the user spends more time interacting with the device, the system can refine its understanding of the user’s normal patterns, improving the accuracy, reliability, and consistency of the Trust Score.

CypherEye operates on the user’s smartphone, which is already associated with the user through existing identity ecosystems such as Apple ID or a Google account. CypherEye binds a CypherID to the device and associates that CypherID with the user’s Trust Score, creating a link between the device, the Trust Score, and the individual.

CypherEye itself is designed to take only minutes to train and configure. The complexity of an enterprise rollout will depend on the organization’s existing infrastructure and implementation requirements.

CypherEye is available on Android and iOS and can be integrated directly into existing Authentication services through an SDK.