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3 ways AI will integrate with DevSecOps

3 ways AI will integrate with DevSecOps

In recent times, many organizations are moving towards AI and ML and getting attracted towards them as it drives the development process in SDLC. We get a lot of benefits from AI, but along with these, we also have to face some dangers, such as in the matter of security. AI believes in training the process based on historical behavior and taking better action when similar situations occur again in the future. There should be some practices that should involve more security practices with AI techniques. It is what is called as DevSecOps. Which will deliver the product faster and with at most security?

Explaining DevSecOps in Detail

It is a study that attempts to integrate security theory into DevOps technologies. In this, the DevOps and Cyber ​​Security teams come on the same page where the agenda is to deliver fast code with utmost security. It bridges the gap between DevOps service providers and the security team that will help make the product more reliable and the delivery pipeline stronger. It follows a microservice-based infrastructure where single-function modules are present instead of complex modules. There will be continuous monitoring of the up-gradation of processes and infrastructure so that the organization does not face any trouble to continue with its new developments. A hybrid cloud environment should be integrated into the infrastructure. Also, a continuous feedback loop will help developers to know their mistakes earlier, and all security breaches can be controlled. With the help of a real-time feedback system, organizations can never make the mistake of putting their systems at risk.

Benefits of using DevSecOps over DevOps

Let’s see the benefits which DevSecOps will provide which were not present in DevOps.

  • Efficiency of product delivery gets increased.
  • More agile processes will be followed that will help in integrating all the teams.
  • Automatic builds for assurance testing will be done easily.
  • If there are any deficiencies, they will be detected early, so that you can take action on them so that those issues do not come up in production.
  • There will be a greater degree of transparency in the procedures followed in the organization.
  • The cloud will become more scalable, and it will not allow more vulnerabilities to lead to production.
  • ROI will get increased.

AI and ML can help DevSecOps by increasing the speed of false-positive identification. It will eventually reduce the time spent on threat vector identification. So let’s see here how DevSecOps can emerge this year with 3 types of support so that IT organizations can start using DevSecOps as enthusiastically as they used to implement AI.

1. Low-security Review time

Earlier developers did not have enough time to inspect the security due to very strict timing guidelines. The developer had very little time to complete development because the code could move quickly into production. They did not bother about the security testing of the product as it was an add-on to the time. The speed and accuracy of AI are tremendous, and developers can do the development at a faster pace so that they can meet guidelines. With the rapid development of AI technologies, security testing can be done without any hassle. With AI and security testing, you can decrease vector identification time, and your delivery pipeline in DevOps will become more speedy.

It will help developers know about the vulnerable risk and the huge impact they will have on the delivery pipeline. You can access the security risk in real-time, and in this way, AI is going to advance DevOps Security testing.

2. Need of Cyber Security Professionals

Cyber-security incidents are increasing at a rapid pace. And it has become very important that we restrict these breaches, or else they can cause huge losses. If you think that AI can completely replace humans, it is a completely false statement. AI also depends on humans because the first process of training requires you to feed some data. This data has to be consolidated by human monitoring, and if you are using the wrong data, then obviously machine would be trained the wrong way. Therefore, it is imperative to fulfill that the correct data is given to the machine to train it properly.

It is important to have more cyber security experts who are able to identify which data is wrong and which is correct, and they should know how to train the AI model. These should be proficient in security testing experience. They should know whether the data is corrupt or not and whether the conclusions are correct or not. Machine learning and AI are highly efficient technologies, but the first step is human input, and if the human is training the model in the right way, then even if these technologies can’t get the correct output.

3. New Learning and Fast Discoveries of Vulnerabilities

AI can be integrated into DevSecOps as it will help developers continuously increase the performance without putting the delivery of the product at stake. With the help of AI, developers can do the development at a faster pace, and in this meanwhile, they can learn from their mistakes. They can learn from their experiences and can avoid these mistakes in the longer run. The developer needs enough time to complete the coding and test the code before putting the code into production, which the AI will give to the developer. With the help of security testing, you can catch security breaches. So, it will help to get rid of all the errors and make the security delivery pipeline very robust.

Conclusion

You can successfully implement AI in DevSecOps by integrating security from the beginning to the ending of the pipeline. Let us tell you that you should always try to implement OWASP Dependency checks like vulnerability Checks and Discovery Tests. You can improve the consistency of the deployments. You can have in place some straight compliance that should be followed, which increases traceability of the pipeline. So, try to adapt AI in DevSecOps and make your processes more security compliant. Your product will be delivered at a faster pace, and with this new advancement in DevSecOps, the customer will be happy. All the best!!

Read More: Reasons Why You Should Always Use sorted() in Python

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