AI-Based Software Reverse Engineering Without Source Code

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Solution Overview

Problem

Conventional software reverse engineering techniques are time-consuming, resource-intensive, and often depend on platform and programming language, making them inefficient when skilled engineers are not available.

Innovation Solution

Utilizing artificial intelligence techniques to predict software outputs and generate supporting information for reverse engineering without examining the source code, through an automated process that includes an input-output sequence processor, multimodal artificial intelligence-based prediction engine, and prediction interpretation engine.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional source code dissection techniques are used for software reverse engineering, then detailed software understanding can be achieved, but the process becomes time-consuming and resource-intensive

Engineering Contradiction:

Improvesoftware understanding accuracyVSAvoidreverse engineering time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical source code dissection with automated artificial intelligence techniques. The AI system processes software artifacts, execution traces, and documentation to generate reverse engineering outputs automatically, eliminating the need for human engineers to manually analyze source code while maintaining comprehensive software understanding.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces AI-generated supporting information as an intermediary between the software artifact and the reverse engineering output. This intermediary includes executed trace data, variable value information, and other contextual data that helps the AI system accurately reconstruct software behavior without requiring direct manual source code analysis.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If skilled engineers are required to perform source code dissection, then accurate reverse engineering can be achieved, but the process becomes dependent on engineer availability and expertise

Engineering Contradiction:

Improvereverse engineering accuracyVSAvoidengineer availability requirement

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The patent enables the software system to reverse engineer itself through automated AI techniques. The system processes its own artifacts, execution traces, and documentation to generate reverse engineering outputs without requiring external human expertise. This self-service approach eliminates dependency on skilled engineer availability while maintaining accuracy through multiple AI analysis pathways.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent creates a universal reverse engineering system that can process multiple types of software artifacts (source code, binaries, documentation, execution traces) and adapt to different software types and platforms. The AI system performs multiple functions including behavior reconstruction, documentation generation, and vulnerability analysis, replacing the need for specialized human expertise across different domains.

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Measurement precision

If conventional reverse engineering techniques are used, then platform-specific and language-specific analysis can be performed, but the process loses adaptability across different platforms and programming languages

Engineering Contradiction:

Improveplatform-specific analysis accuracyVSAvoidplatform agnosticism

Core Design Contradiction:

Measurement precisionVSAdaptability or versatility

Solution Approach 1:

The patent implements a universal AI-based reverse engineering system that can process software artifacts from multiple platforms and programming languages through a single unified approach. The system analyzes execution traces, variable values, and software behavior rather than relying on language-specific syntax or platform-specific conventions, enabling cross-platform and cross-language adaptability while maintaining analysis accuracy.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent changes the analysis parameters from source code syntax and structure (which are language-specific) to execution behavior, trace data, and runtime characteristics (which are platform-agnostic). By focusing on observable software behavior rather than implementation details, the system achieves versatility across different platforms and programming languages while maintaining precise reverse engineering capability.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20250321721A1Context-based software engineering using artificial intelligence techniques

Publication Date: 2025.10.16 DELL PROD LP

AI summary

Methods, apparatus, and processor-readable storage media for context-based software engineering using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining input data associated with at least one software program; predicting one or more outputs which can be generated by the at least one software program, in response to at least a portion of the input data, by processing the input data using one or more artificial intelligence techniques; generating one or more items of supporting information attributed to at least a portion of the one or more predicted outputs; and automatically reverse engineering at least a portion of the at least one software program using at least one of the one or more predicted outputs and the one or more items of supporting information.