The rapid growth and increasing complexity of Python based web applications and systems have made robust security testing more important than ever.
Cyber criminals are constantly evolving their tactics, looking for vulnerabilities they can exploit to steal data or disrupt operations. Traditional security testing for Python applications is still complex, time-consuming, and expensive.
(more…)A single tool, suite or framework to manage all aspects for security aspects is in practice impossible. There are far too many aspects that require specialist tools and expertise that creating and maintaining such a tool is impossible. Also the code-base will be insecure by design, since security maintenance of large complex code bases is in practice impossible.
Good measurements for cyber security do not have to be technical. From a defence in depth principle it is recommended to have a mix of various technical and non technical measurements. A healthy distrust in security means never trust software and hardware and take as many measurements to mitigate cyber risks to acceptable levels.
(more…)Python is for one of the most used programming language to date. Especially in the AI/ML world ecosystem, most tools are based on Python programs. Large and small businesses use and trust Python to run their business. Python is from security perspective a safe choice. However even when using Python the risk on security issues is never zero.
When creating solutions practicing Security-By-Design to prevent security issues is still needed.
(more…)What happened with blockchain technology is also happening with AI technology. Too many people believe that it is a solution for all hard and complex problems. I still love this flowchart that helps you to determine if blockchain is an appropriate technology for your use case. Spoiler: Blockchain is seldom a solution.
(more…)If you want to keep complexity low and minimize security risks, you always need to decide whether using an external Python library is the right choice.
Practising 0Complexity design principles is never easy. But when it comes to security and minimising dependencies, you should weigh the advantages and disadvantages of using any external Python library.
Don’t get me wrong: many FOSS Python libraries are excellent, well-maintained software and you’d be foolish not to use them when appropriate.
So before using a new module in an MVP, running a quick and simple Static Application Security Test (SAST) on the external Python module will provide valuable information from a security point of view.
(more…)Python is for one of the most used programming language to date. Especially in the AI/ML world and the cyber security world, most tools are based on Python programs. Large and small businesses use and trust Python to run their business. However even when using Python the risk on security issues is never zero. Static application security testing (SAST) tools , like Python Codeaudit program should be used to prevent security risks or to be aware of potential risks that comes with running the software.
(more…)Cyber security is complex. But effective cyber solutions do not need to be complex and very expensive.Simplifying your security landscape is not simple, it means rethinking your strategy and re prioritizing objectives. The perfect solution to reduce security risks to zero does not exist. But using and creating a security architecture helps with reducing and managing your risks. A good way to really speed up creating your solution architecture is to use this reference architecture as the basis.
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