AI is everywhere now! We are embedding AI into our browsers, emails, document management systems, and more. We are literally giving AI the power to work instead of us.
Everywhere, there is a shout that if you are not going to use AI now, you will be left behind. But is it okay to leverage AI without knowing its real cyber security issues and the ways to overcome that.
That is what I have done here. This blog discussed the risks and strategies needed to use generative AI in software development. The reasons are collected based on the research.
Risks of utilizing generative AI in software development
The cybersecurity issues involved in using a generative AI that could risk errors in software development are covered here.
Improper development process
In today’s fast pace of software development, companies are deploying AI tools quickly, which is unprecedented in the digital world. Normal control of software development and lifecycle management is not always present.
Adrian Volenik, the founder of aigear.io thoughts on this is, nowadays, it is incredible to show the app as an AI app even though it has been developed in a one day without oversight or care about the privacy, security or even anonymity of the users. This problem induced a risk of using the application from the user side.
High risk of identity theft and data breaches
As a user, when we share our information using the app, we trust and affirm the safe handling of data with robust security functions by the company. We literally trust them.
But in the case of using generative AI apps, we are sharing unintentionally more than we think. The founder and CEO of Copymatic, Ryan Faber thoughts on this is we are giving every detail to AI, and it is utilizing the data in whichever way it can to enhance the user experience. The lack of proper procedure in how the data has been collected, utilized or dumped raises serious concerns in the world of software development.
AI is complex and has poor security
Any new app that is added to a network introduces new vulnerabilities that may be used to access other parts of your network. Because they feature complicated algorithms that make it challenging for developers to find security problems, generative AI apps present a special danger.
AI’s code is susceptible since it is not yet developed enough to comprehend the many details of software development. Nearly 40% of the most important AI ideas and 40% of all AI proposals, according to research evaluating the security of code created by GitHub Copilot, resulted in vulnerabilities in the code. The researchers also discovered that non-semantic, minor adjustments like comments might affect code safety.
Risk of exposing confidential information
If you’ve been experimenting with AI tools for a while, you’ve undoubtedly already discovered how important crafting a strong prompt is for achieving effective outcomes. For the best answer, you give context and background data to the AI chatbot.
You can give the AI chatbot access to private or proprietary information, which is bad. Data security company Cyberhaven conducted research and discovered
Employees paste 11% of their private information into ChatGPT.
At least once, 4% of employees have copied critical information into it.
Intellectual property, confidential strategic information, and client data are shared among the staff. This has raised issues for organizations in leaking their personal information and losing data privacy.
Misuse of deepfakes
As an access control security precaution, voice and face recognition are becoming more prevalent. AI presents a chance for criminals to develop deepfakes that circumvent such security.
Strategies to strengthen the security posture against generative AI risks
There are some ways to counter the risks, few of them are covered here
Research the company behind the app
With its various tools and services, an app’s reputation and performance history may be assessed. But never assume that a well-known brand guarantees a sufficient degree of protection.
Review the company’s security measures and privacy policies as well. If you provide information to an AI tool, it may be included to its large language model (LLM), making it possible for it to appear in replies to questions posed by other users. You can request an attestation letter that details the app’s security status in order to verify its reputation and security features.
Educate employees to use AI tools properly and safe
You should already be educating staff on basic cybersecurity practices in addition to having standards in place for permissible social media usage. The framework needs to be updated with some additional training subjects and policies as generative AI technologies become more widely used. These may consist of:
- What they may and cannot divulge to applications that use generative AI
- a general description of the operation of LLMs and the dangers in utilising them
- limiting the usage of authorised AI apps on business devices
- Implement security measures to stop oversharing.
We’ll soon witness a burgeoning set of cybersecurity technologies created expressly for the vulnerabilities of generative AI systems as their manufacturing continues. To keep track of which AI software are currently connecting to your network, you may also utilize a network auditing tool.
Badman too uses AI
Everyone seeks the advantage. AI technologies aren’t simply for diligent people or ethical hackers. The sorts of harmful activities that we already need to be protected against are being improved and scaled up by bad actors utilising AI and generative AI technologies.
Generic AI is also used by hackers. They have a better chance of getting past network security technologies if they readily build a large number of spoof websites, each of which differs just slightly from the others.
The time has come to strengthen your traditional cybersecurity defenses since AI is assisting hackers in improving their classic schemes.
Update your operating system and applications. Hackers now have far easier access to exploit known flaws.
Deploy end-to-end protection software
Strengthen credentials. Combined with multi-factor authentication, use strong passwords. If one is available, consider forgoing passwords in favor of passkeys.
As part of your business continuity strategy, set up a data and application backup solution to ensure that you can continue to operate in the event of a ransomware or other attack. Teach security-conscious behaviors to both you and your staff.
Hence in conclusion
Just learn the ways to counter the risk of AI rather than being a victim of it. AI is the next-generation tool that is surely going to revolutionize the digital world. This is not the debate to avoid generative AI, but an initiative to inform the risks and precautions needed to take to enjoy the AI leverages by forming a powerful cybersecurity wall around us.