Potential for iPhone eKYC Hacking: How “Passcode Shouldering,” “Selfies,” and a Few Minutes…

[Editor’s Note]

• Part 1 : When Authorization Breaches Availability: The 27.2KB iCloud Anomaly
• Part 2 : AI is Not a Translator, It’s Your Chief of Staff: Winning a 120-Hour Logic War Against Apple
• Part 3 : CVEs as “Feature Catalogs”: The Terrifying Reality of Automated, Version-Specific Exploit Kits Targeting iOS 18.5

Note on scope and assumptions

This article is written as a continuation of my previous report, which discusses the possible existence of tools that automate the chaining of known iOS vulnerabilities based on OS version detection.

This analysis is hypothetical and based on assumed toolchains for illustrative purposes only.

No known publicly available exploit for Face ID or eKYC systems is confirmed to work as described in real-world deployments

1. Introduction: Incident Overview and Purpose

This paper presents a technical analysis based on the examination of iOS diagnostic logs (.ips) concerning specific anomalous incidents observed on the device: an “iCloud 27.2KB sync mismatch” and a “genuine camera unknown part warning.”

From a forensic perspective, this paper investigates the possibility that an eKYC bypass scenario using “Virtual Camera” spoofing — combining physical compromise and known vulnerabilities — underlies these events, which might initially appear to be simple hardware malfunctions or user errors.

2. Attack Scenario: Convergence of Social Engineering and Technical Compromise

Any sequence of actions described here depends on unrealistic, highly constrained conditions that are rarely satisfied in modern operational environments.

The exploit chain hypothesized in this analysis consists of the following three steps:

(1) Privilege Acquisition (Shoulder Surfing)

During a social setting like a meal, an attacker subtly observes your hands as you unlock your device. Alternatively, they may induce passcode entry by prompting actions such as propping up the smartphone to watch a video. This “seizure of the passcode” enables all subsequent physical interventions.

(2) Collection of Training Material (Two-Shot Photos)

Requesting frequent photos together is a tactic to collect high-precision facial data from multiple angles, which is then used to generate deepfake videos.

(3) Physical Intervention and Tool Injection (The Minutes Left Unattended)

When the device is left unattended, the attacker uses the stolen passcode to perform physical intervention (e.g., connecting hardware programmers like JCID or executing DMA attacks via Lightning/USB-C ports). Even on non-jailbroken devices, attackers can chain known kernel vulnerabilities to inject code into the camera control processes.

3. Technical Analysis of Diagnostic Logs

The following anomalies extracted from .ips logs indicate behaviors that are difficult to explain through standard OS operations.

A. Abnormal Frequency of copyonwritefaults

High counts of copyonwritefaults in the stackshot logs suggest intense process contention for specific memory regions. This supports the hypothesis that an unauthorized process attempted to forcibly overwrite the legitimate camera video buffer (Cameracaptured) to inject spoofed video frames.

B. bug_type 288 and System Time Discontinuity

Second-level time jumps (system clock manipulation) recorded in the logs are likely traces of a virtual camera tool manipulating the system clock to bypass video call app timeouts or fake license authentications.

• bug_type 288 (Stackshot): Indicates the system generated a snapshot of all running processes. If generated without user intent, it suggests a system hang or an external tool forcibly scanning internal states.
• Time Discontinuity: Significant jumps in the system clock suggest physical intervention (battery disconnection, hardware programmer use) or intentional manipulation to skip passcode lockout timers.

C. Interference Between Cameracaptured and Evidence Erasure

The fact that the camera process remained active while an evidence erasure process was running suggests that a virtual camera tool was hijacking the system until immediately after the attack was completed.

The “iCloud 27.2KB sync mismatch” is likely the result of a database corruption occurring when the erasure process attempted to overwrite logs while the system was still writing to them (SQLite WAL mode conflict).

4. iOS 18 Integrity Checks and “Unknown Part” Warnings

Even when external tools like 3uTools report hardware serial numbers as “Normal,” iOS 18 may still trigger an “Unknown Part” warning.

Modern iOS security mechanisms monitor the integrity of the communication path between hardware and software. When a virtual camera tool hooks this communication, the OS detects inconsistencies in encrypted signature data, causing the software-level spoofing to manifest as a hardware integrity error.

5. Mechanism for Bypassing “Liveness Detection” via Virtual Camera

Mainstream eKYC “Liveness Detection” requires users to perform random actions (e.g., turn right, blink, smile). Virtual camera attacks bypass these checks through the following flow:

1. Real-time Injection: Attackers pre-generate deepfake patterns for various movements. The tool triggers the corresponding video file into the camera buffer as the app requests specific actions.
2. Environmental Consistency: Advanced tools synchronize spoofed video with the device’s gyroscope and ambient light sensors to deceive the app’s spatial algorithms.
3. Depth Simulation: For apps requiring facial depth, attackers use physical camera connector hooking to overwrite raw sensor data, faking 3D consistency.

6. Conclusion: The Need for Architectural Resilience

While this scenario remains a hypothesis based on limited logs, it serves as a profound example of how physical compromise can undermine software trust.

Apple’s concept of “Authorized” operations can be neutralized by a chain of physical access and vulnerabilities. Once a passcode is stolen and physical access is granted, attackers can bypass the OS’s “trust in hardware” via kernel-level intervention. When the “physical reality” captured by the sensor is decoupled from the “digital reality” perceived by the OS, the system loses its ability to detect deception.

System architects must move beyond blind faith in device integrity. We must reconstruct Defense in Depth based on end-to-end consistency verification on the cloud side and fine-grained hardware anomaly detection.

The key takeaway is not feasibility, but the importance of layered controls, delayed actions, and risk-aware workflow design when using eKYC for sensitive operations.

The key takeaway is not whether such scenarios are theoretically possible,but how identity verification systems should be designed assuming that no single control is infallible.

From a defensive perspective, the discussion highlights the importance oflayered safeguards, delayed critical actions, and risk-based decision makingwhen eKYC is used as part of sensitive workflows.

About the author

Ryu360 is a system architect and digital forensics specialist who focuses on uncovering structural security failures hidden behind formally “correct” system designs.

He analyzes real-world anomalies through forensic logs, behavioral inconsistencies, and adversarial architectural reasoning, with particular focus on identity-related systems such as iOS, Apple ID, Passkeys, and eKYC.

He has independently identified integrity anomalies within iCloud systems and engaged directly with Apple Product Security regarding architectural-level security issues.

His work centers on security design review, forensic analysis, and structural risk assessment rather than conventional software development.

If you believe your system or architecture may be affected by similar structural risks, you can contact him here:
👉 Consultation / Technical Inquiry Form
https://forms.gle/btGiwS9ZRc3XhZL37

(All requests are reviewed individually. Some engagements may involve paid advisory work.)