The software supply chain is crucial to bringing new and upgraded applications to market. Here’s how AI helps keep it secure.
SwissCognitive Guest Blogger: Zachary Amos – “Securing the Software Supply Chain With AI”
Developers can use AI to strengthen software supply chain security in several powerful ways. There are many libraries, devices, users and datasets to keep track of in any software program’s supply chain, which creates numerous security challenges. AI offers a solution thanks to its adaptability and pattern-recognition capabilities.
What Is the Software Supply Chain?
The software supply chain includes all the businesses, developers, suppliers and third-party partners that work together to bring a new application to market. The various components in this supply chain include in-house code a company writes from scratch, security code, open-source libraries and frameworks, testing tools, UX/UI content, and more.
Here’s how AI steps in to improve software supply chain security.
1. Improved Endpoint Security
Endpoints are some of the most common entryways for cyber attacks and are notoriously difficult to secure. These are devices like individual phones or laptops where users access components of the software supply chain. They’re dispersed and typically subject to whatever security measures a particular user has in place.
AI can help secure endpoints throughout the software supply chain. For example, developers and supply chain partners can use AI to scan endpoint devices for malicious files autonomously, such as malware. AI can also monitor activity across many endpoints at once and report suspicious behavior. Both functions enable AI to make endpoints significantly stronger frontline defenses against cyber attacks.
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2. Adaptive Automated Threat Detection
One of the best benefits of AI for software supply chain security is its adaptability. Thanks to machine learning, AI can update its responses in real time as it encounters new risk factors. This makes it a powerful tool for automated threat detection.
For example, AI can help protect DevOps teams, software developers and supply chain employees by autonomously detecting phishing content. Phishing is a common tool hackers use to steal data and launch malware attacks. It involves sending victims messages that appear legitimate but contain malicious links.
AI is great at pattern recognition — an important part of identifying phishing content. Even if a user is fooled by a phishing message, the AI can immediately detect it and warn them the link is unsafe. Features like this could significantly reduce the number of successful phishing attacks, which are often precursors to more dangerous ransomware attacks.
Additionally, adaptive AI threat detection is excellent for preventing zero-day attacks. In this type of cyber attack, hackers exploit vulnerabilities in a new piece of software before developers know about them. Zero-day attacks are notoriously difficult to stop due to all the unknowns.
One of the major drawbacks of conventional security tools is they need to know what to look for. They only work for attacks they’ve seen before, so new, unknown threats can often get past traditional cybersecurity tools.
This isn’t the case with AI. Algorithms look for activity that breaks patterns rather than file types or red flags. As a result, it can stop new kinds of attacks it’s never seen before.
3. Cost Reduction
One of the most harmful impacts of cyber attacks in the software supply chain is the significant loss of money they cause. The average cost of a data breach increased 13% between 2022 and 2023, with an emphasis on recovery-related expenses. Prices are significantly higher if victims pay hackers ransoms for their data, which is strongly discouraged.
AI can help supply chain organizations minimize or eliminate cyber attack-related costs. By preventing successful attacks, AI reduces the threat hackers pose. Even in cases where an attack is successful, AI can minimize the damage through early detection and automated defense mechanisms.
AI-powered security can save money in less tangible but equally important ways, as well. For instance, software supply chain businesses can lose revenue due to a loss of customer trust after a cyber attack. Their insurance rates are also likely to increase. Advanced AI security bolsters trust for customers and insurance agencies by demonstrating a developer uses the most powerful cybersecurity tools available.
4. Compliance Verification
Security compliance is increasingly important today as governments ensure businesses protect themselves and their customers. Unfortunately, verifying compliance in a large, disparate software supply chain can be difficult.
This is a great opportunity to apply AI’s excellent pattern-recognition capabilities. AI can automate analyzing supply chain parties’ security measures for key compliance factors. Businesses can also use AI to monitor vendors’ and suppliers’ behavior over time to verify they are sticking to security regulations between audits.
Doing so is extremely important since third parties can pose a severe security risk in today’s supply chain. For example, in 2022, Okta — a major supplier of identity-management services — suffered a significant data breach originating from a third-party’s network. Many similar cases have occurred over the years, such as the infamous 2013 Target data breach involving a supplier.
Third-party partners, vendors and suppliers often need to employ effective security measures. AI can help software supply chain businesses ensure they’re only working with secure partners so they can protect their data, products and customers.
5. Predictive Analytics and Modeling
Developers can use AI to predict potential cyber attacks before hackers launch them, allowing developers to eliminate risks in advance. AI is a powerful tool for predictive modeling. It can analyze every aspect of a software program and identify ways a hacker might try to exploit different features. By modeling possible attacks, developers can stay one step ahead of hackers.
This applies to the software supply chain itself, as well. Attacks on supply chain businesses are getting increasingly common since hackers know supply chain delays are crippling for many organizations. AI-powered predictive analytics can help supply chain businesses anticipate potential issues so they can plan for or avoid them altogether.
How AI Strengthens Software Supply Chain Security
AI is the cutting edge of software supply chain cybersecurity. With machine learning, pattern recognition and predictive analytics, AI can predict, detect and stop cyber attacks. AI can even identify completely new types of attacks. Algorithms’ ability to adapt as the risk landscape changes allows developers to use AI to stay ahead of hackers and protect their supply chains.
About the Author:
Zachary Amos is the Features Editor at ReHack, where he writes about artificial intelligence, cybersecurity and other technology-related topics.
The software supply chain is crucial to bringing new and upgraded applications to market. Here’s how AI helps keep it secure.
SwissCognitive Guest Blogger: Zachary Amos – “Securing the Software Supply Chain With AI”
What Is the Software Supply Chain?
The software supply chain includes all the businesses, developers, suppliers and third-party partners that work together to bring a new application to market. The various components in this supply chain include in-house code a company writes from scratch, security code, open-source libraries and frameworks, testing tools, UX/UI content, and more.
Here’s how AI steps in to improve software supply chain security.
1. Improved Endpoint Security
Endpoints are some of the most common entryways for cyber attacks and are notoriously difficult to secure. These are devices like individual phones or laptops where users access components of the software supply chain. They’re dispersed and typically subject to whatever security measures a particular user has in place.
AI can help secure endpoints throughout the software supply chain. For example, developers and supply chain partners can use AI to scan endpoint devices for malicious files autonomously, such as malware. AI can also monitor activity across many endpoints at once and report suspicious behavior. Both functions enable AI to make endpoints significantly stronger frontline defenses against cyber attacks.
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
2. Adaptive Automated Threat Detection
One of the best benefits of AI for software supply chain security is its adaptability. Thanks to machine learning, AI can update its responses in real time as it encounters new risk factors. This makes it a powerful tool for automated threat detection.
For example, AI can help protect DevOps teams, software developers and supply chain employees by autonomously detecting phishing content. Phishing is a common tool hackers use to steal data and launch malware attacks. It involves sending victims messages that appear legitimate but contain malicious links.
AI is great at pattern recognition — an important part of identifying phishing content. Even if a user is fooled by a phishing message, the AI can immediately detect it and warn them the link is unsafe. Features like this could significantly reduce the number of successful phishing attacks, which are often precursors to more dangerous ransomware attacks.
Additionally, adaptive AI threat detection is excellent for preventing zero-day attacks. In this type of cyber attack, hackers exploit vulnerabilities in a new piece of software before developers know about them. Zero-day attacks are notoriously difficult to stop due to all the unknowns.
One of the major drawbacks of conventional security tools is they need to know what to look for. They only work for attacks they’ve seen before, so new, unknown threats can often get past traditional cybersecurity tools.
This isn’t the case with AI. Algorithms look for activity that breaks patterns rather than file types or red flags. As a result, it can stop new kinds of attacks it’s never seen before.
3. Cost Reduction
One of the most harmful impacts of cyber attacks in the software supply chain is the significant loss of money they cause. The average cost of a data breach increased 13% between 2022 and 2023, with an emphasis on recovery-related expenses. Prices are significantly higher if victims pay hackers ransoms for their data, which is strongly discouraged.
AI can help supply chain organizations minimize or eliminate cyber attack-related costs. By preventing successful attacks, AI reduces the threat hackers pose. Even in cases where an attack is successful, AI can minimize the damage through early detection and automated defense mechanisms.
AI-powered security can save money in less tangible but equally important ways, as well. For instance, software supply chain businesses can lose revenue due to a loss of customer trust after a cyber attack. Their insurance rates are also likely to increase. Advanced AI security bolsters trust for customers and insurance agencies by demonstrating a developer uses the most powerful cybersecurity tools available.
4. Compliance Verification
Security compliance is increasingly important today as governments ensure businesses protect themselves and their customers. Unfortunately, verifying compliance in a large, disparate software supply chain can be difficult.
This is a great opportunity to apply AI’s excellent pattern-recognition capabilities. AI can automate analyzing supply chain parties’ security measures for key compliance factors. Businesses can also use AI to monitor vendors’ and suppliers’ behavior over time to verify they are sticking to security regulations between audits.
Doing so is extremely important since third parties can pose a severe security risk in today’s supply chain. For example, in 2022, Okta — a major supplier of identity-management services — suffered a significant data breach originating from a third-party’s network. Many similar cases have occurred over the years, such as the infamous 2013 Target data breach involving a supplier.
Third-party partners, vendors and suppliers often need to employ effective security measures. AI can help software supply chain businesses ensure they’re only working with secure partners so they can protect their data, products and customers.
5. Predictive Analytics and Modeling
Developers can use AI to predict potential cyber attacks before hackers launch them, allowing developers to eliminate risks in advance. AI is a powerful tool for predictive modeling. It can analyze every aspect of a software program and identify ways a hacker might try to exploit different features. By modeling possible attacks, developers can stay one step ahead of hackers.
This applies to the software supply chain itself, as well. Attacks on supply chain businesses are getting increasingly common since hackers know supply chain delays are crippling for many organizations. AI-powered predictive analytics can help supply chain businesses anticipate potential issues so they can plan for or avoid them altogether.
How AI Strengthens Software Supply Chain Security
AI is the cutting edge of software supply chain cybersecurity. With machine learning, pattern recognition and predictive analytics, AI can predict, detect and stop cyber attacks. AI can even identify completely new types of attacks. Algorithms’ ability to adapt as the risk landscape changes allows developers to use AI to stay ahead of hackers and protect their supply chains.
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