Abstract digital data forensic visualization
Case Study — Digital Forensics & Analysis

STEGSCAN

A forensic toolkit engineered to detect statistical anomalies, expose LSB manipulation, and extract malicious payloads hidden in plain sight.

Hidden in Plain Sight.

Threat actors increasingly bypass perimeter defenses and static analysis by embedding malicious scripts, C2 instructions, and data exfiltration payloads within seemingly benign image and audio files. StegScan was developed to tear down this camouflage.

Deep Inspection Bit-Level Analysis
Extraction Payload Recovery
Hex code and binary data

Forensic Methodologies.

analytics

Statistical Analysis

Utilizes Chi-Square attack algorithms and entropy measurement to detect the statistical anomalies introduced when a file's natural noise is replaced by encrypted data.

grid_on

LSB Extraction

Automated parsing of the Least Significant Bits across RGB channels to reassemble hidden bitstreams and isolate embedded executables or text.

find_in_page

Structural Audits

Deep structural verification checking for appended EOF (End of File) data, corrupted chunk headers, and manipulated EXIF manipulation.

The Stack.

Built for speed, accuracy, and seamless integration into larger forensic pipelines.

Py Python 3
CV OpenCV / PIL
Np NumPy Arrays
terminal CLI Architecture
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