Visualizes AWS IAM and Organizations as a graph using Neo4j to identify security anomalies and privilege escalation paths.
Aaia is an open-source security tool that visualizes AWS Identity and Access Management (IAM) and Organizations data as a graph using Neo4j. It helps security professionals and cloud administrators identify anomalies, privilege escalation paths, and misconfigurations by representing IAM relationships visually, moving beyond traditional list-based IAM analysis.
Cloud security engineers, AWS administrators, and penetration testers who need to audit and visualize AWS IAM configurations for security risks.
Developers choose Aaia because it provides a graph-based approach to IAM analysis, making complex relationships and security outliers easier to detect compared to native AWS tools or other list-based audit solutions.
AWS Identity and Access Management Visualizer and Anomaly Finder
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Transforms AWS IAM and Organizations data into a Neo4j graph, making complex relationships and policy attachments visually intuitive, as shown in the provided screenshots.
Helps identify security outliers and privilege escalation paths by analyzing graph relationships, inspired by the principle that 'defenders think in lists, attackers think in graphs.'
Provides a framework for building Python modules to perform programmatic data processing and complex logic beyond basic Cypher queries, as evidenced by the sample module in the repository.
Includes a shell script to collect AWS IAM and Organizations data for analysis in disconnected environments, useful for consulting or client audits as mentioned in the README.
The repository is not under active development, with the author only accepting PRs and no significant updates, which could lead to compatibility issues and lack of new features over time.
Only tested with Neo4j v3.5.17 and not compatible with versions post v4.0, limiting adoption for teams using newer Neo4j releases, as explicitly stated in the installation notes.
Not supported for Windows OS due to unstable pyjq dependency, restricting its use to Linux or macOS environments, which narrows the user base.
Requires manual installation of Neo4j (via Docker or binary), configuration of AWS permissions, and dependency setup, making initial deployment more involved than integrated cloud tools.