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Why Aura? While there are other tools with functionality that overlaps with Aura such as Bandit, dlint, semgrep etc. the focus of these alternatives is different which impacts the functionality and how they are being used. These alternatives are mainly intended to be used in a similar way to linters, integrated into IDEs, frequently run during the development which makes it important to minimize false positives and reporting with clear actionable explanations in ideal cases. Aura on the other hand reports on ** behavior of the code**, anomalies, and vulnerabilities with as much information as possible at the cost of false positive. There are a lot of things reported by aura that are not necessarily actionable by a user but they tell you a lot about the behavior of the code such as doing network communication, accessing sensitive files, or using mechanisms associated with obfuscation indicating a possible malicious code. By collecting this kind of data and aggregating it together, Aura can be compared in functionality to other security systems such as antivirus, IDS, or firewalls that are essentially doing the same analysis but on a different kind of data (network communication, running processes, etc). Here is a quick overview of differences between Aura and other similar linters and SAST tools: input data: Other SAST tools - usually restricted to only python (target) source code and python version under which the tool is installed. Aura can analyze both binary (or non-python code) and python source code as well. Able to analyze a mixture of python code compatible with different python versions (py2k & py3k) using the same Aura installation. reporting: Other SAST tools - Aims at integrating well with other systems such as IDEs, CI systems with actionable results while trying to minimize false positives to prevent overwhelming users with too many non-significant alerts. Aura - reports as much information as possible that is not immediately actionable such as behavioral and anomaly analysis. The output format is designed for easy machine processing and aggregation rather than human readable. configuration: Other SAST tools - The tools are fine-tuned to the target project by customizing the signatures to target specific technologies used by the target project. The overriding configuration is often possible by inserting comments inside the source code such as # nosec that will suppress the alert at that position Aura - it is expected that there is little to no knowledge in advance about the technologies used by code that is being scanned such as auditing a new python package for approval to be used as a dependency in a project. In most cases, it is not even possible to modify the scanned source code such as using comments to indicate to linter or aura to skip detection at that location because it is scanning a copy of that code that is hosted at some remote location. Authors & Contributors Martin Carnogursky - Initial work and project lead - https://is.muni.cz/person/410345 Mirza Zulfan - Logo Design - https://github.com/mirzazulfan Donate GitHub Sponsors: https://github.com/sponsors/RootLUG Liberapay: https://liberapay.com/SourceCode.AI BuyMeACoffee: https://www.buymeacoffee.com/SourceCodeAI BTC: 3FVTaLsLwTDinmDjPh3BjS1qv3bYHbkcYc XMR: 46xvWZGCexo1NbvjLMMpLB1GhRd819AQr8eFPJT1q6kKMuuDy43JLiESh9XUM3asjk4SVUYqGakFVQZRY1adx8cS6ka4EXr ETH/ERC20: 0x708F1A08E3ee4922f037673E720c405518C0Ec85 LICENSE Aura framework is licensed under the GPL-3.0. Datasets produced from global scans using Aura are released under the CC BY-NC 4.0 license. Use the following citation when using Aura or data produced by Aura in research: @misc{Carnogursky2019thesis,
AUTHOR = "CARNOGURSKY, Martin",
TITLE = "Attacks on package managers [online]",
YEAR = "2019 [cit. 2020-11-02]",
TYPE = "Bachelor Thesis",
SCHOOL = "Masaryk University, Faculty of Informatics, Brno",

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