Security engineering · Egothor × Accenture
MethodAtlas
A reproducible, audit-friendly inventory of test methods in a codebase, with optional AI-assisted security classification and evidence workflows designed for regulated software delivery.
Why MethodAtlas exists
Passing tests answer whether a suite succeeded. They do not automatically explain which security properties are exercised, which controls are represented, what changed since the last review or how an auditor can reproduce the evidence. MethodAtlas turns test source into a structured inventory and then layers classification, review and evidence workflows on top.
The architecture deliberately separates deterministic discovery from optional AI interpretation. Test methods are found from source using language-aware parsers; AI can enrich those records, but it does not define whether a method exists.
Core capabilities
Source-level inventory
Discovers tests without compiling or loading application code, across Java, C#, TypeScript/JavaScript, Go, Python, PowerShell, SAP ABAP and COBOL.
Security classification
Optional local or cloud AI classification adds security relevance, taxonomy tags, rationale and confidence while keeping the deterministic inventory intact.
CI-native output
CSV, plain text, SARIF 2.1.0, GitHub Actions annotations and JSON fit common assurance and developer workflows.
Reproducibility receipts
Configuration, taxonomy, models and effective prompt templates can be fingerprinted so a review can establish what influenced a result.
Control coverage
Test tags can be mapped to team-defined controls to expose assurance gaps rather than merely count tests.
Evidence integrity
Evidence packs can be made tamper-evident and signed with classical, post-quantum or hybrid signatures.
Deterministic core, controlled AI
MethodAtlas supports local Ollama inference, multiple cloud providers and a two-phase manual workflow for environments where direct API connectivity is not acceptable. The design keeps source discovery reproducible and makes AI an explicit enrichment stage rather than a hidden dependency.
A separate credential-detection mode uses deterministic pattern matching for candidate discovery, masks values by default and can optionally use AI to score credibility and associate a candidate with an endpoint.
Collaboration and license
MethodAtlas is published in the Accenture GitHub organisation and carries copyright notices for Egothor and Accenture. The project is licensed under the Apache License, Version 2.0.