BackBox Principles for Responsible Artificial Intelligence (AI)

Artificial Intelligence (AI) has undergone significant evolution over the years, presenting both exciting opportunities and unique challenges for businesses. Cybercriminals can now identify vulnerabilities in record time — within days, rather than months or years — creating a pressing need for enhanced defenses. Fortunately, AI has emerged as a powerful ally in bolstering network cyber resilience. It enables faster response times and more efficient resource allocation, significantly reducing alert fatigue while allowing teams to focus on targeted remediation strategies.

The rapid rise of AI presents fantastic prospects, yet it also prompts us to consider essential issues such as privacy, transparency, and ethics. Questions about the reliability of certain AI algorithms and the potential for misuse highlight the importance of maintaining trust in this transformative technology.

Currently, AI excels where minor errors are acceptable. Still, we must remember that it’s not yet ready for deterministic operations — especially when high service-level requirements are in place, as we strive to avoid outages.

Because accuracy and reliability depend on the data behind these systems, it’s crucial to understand what fuels AI systems. Concerns arise when proprietary data is shared, even if it is anonymized. In contrast, leveraging AI on publicly accessible information — like network vendor vulnerability sites — can provide valuable, actionable insights in a responsible and trustworthy manner.

GUIDING PRINCIPLES FOR ARTIFICIAL INTELLIGENCE

AI is here to stay, and we’re optimistic about what its evolution means for the future. To ensure responsible progress, leading network automation vendors must step up and adopt thoughtful AI strategies that harness this technology for meaningful advancements. This is precisely why BackBox has set forth guiding principles that reflect our unwavering commitment to the ethical development and deployment of AI.

• Building trustworthy AI that emphasizes responsibility, safety, and security.
• Confirming consistent and accurate results while continuously enhancing the AI’s performance and the reliability of its outputs.
• Ensuring human-centered control by viewing AI as a trusted advisor rather than the sole decision-maker.
• Providing transparency in how AI generates responses and recommendations and making data clear and accessible to all stakeholders.

AI AT BACKBOX

AI is not new to BackBox. We have adopted intentional and carefully planned strategies for the ethical development and deployment of artificial intelligence, machine learning, and intelligent automation to enhance the capabilities of our platform.

Enriched Data Aggregation

BackBox uses AI to provide contextual information about CVE severity through a data feed that pulls data from CISA, NVD, NIST, and vendor websites. Instead of visiting multiple sites to learn about the latest vulnerabilities, BackBox users have a single, unified source of truth for vulnerabilities found on devices within their network infrastructure. This enables network engineers to prioritize remediation based on potential impact, without wasting time determining which vulnerabilities apply to their devices.

BackBox only lists CVEs that apply to the specific make, model, and operating system version of the devices on your network. Additionally, BackBox provides a prioritized list of vulnerabilities, highlighting which CVEs are currently being exploited in the wild. We display CVE scores for all devices associated with a particular vendor and product version.

This information allows you to review and prioritize your mitigation strategy across your environment, helping you reduce the highest risks in the shortest amount of time. With BackBox, you gain a level of context that would be difficult to achieve through manual processes.

CVE Workaround Insights

With BackBox, you can explore each CVE in detail, including information on workarounds and a link to the vendor’s actual workaround details. By consolidating this information, BackBox offers a single point of access to the data you need, regardless of the number of devices from different vendors. Additionally, we provide explicit provenance to ensure you are well informed about the source of the data we are providing. This helps to prove authenticity and quality, while making your work much easier. 

The information provided in workaround data is often brief and lacks context, making it difficult to address specific vulnerabilities effectively. BackBox leverages AI and machine learning to analyze vendor workarounds, transforming their content into a standardized format. This process ensures consistent field names and content, while also reintroducing valuable context. As a result, you can make quick and informed decisions.

Read about AI and Network Automation: https://backbox.com/blog/ai-and-automation-key-pillars-for-building-cyber-resilience/ 

Learn more about our AI-enabled Vulnerability Intelligence capabilities: https://backbox.com/vulnerability-intelligence/ 

See BackBox in action: https://backbox.com/request-a-demo/