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How Blackbird AI is striking back at ChatGPT and AI-based attacks  


Feb 20, 2023
How Blackbird AI is striking back at ChatGPT and AI-based attacks  


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For months after the start of OpenAI’s ChatGPT in November 2022, there is been a energetic debate about the probable impact that generative AI will have on business stability. Even though some warn of the hazard of this technology becoming made use of to create malware and phishing content material, some others spotlight how it can automate stability ops. 

A person organization wanting to use generative AI to counter offensive intelligence functions is defensive AI and chance intelligence supplier Blackbird AI, which most not too long ago elevated $10 million in collection A funding in 2021, and currently declared the launch of RAV3N Copilot, an AI assistant for safety analysts. 

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RAV3N Copilot uses generative AI to create narrative intelligence and risk reports to offer defenders greater context for security incidents. It can automatically generate executive briefings, key findings and mitigation steps to help security teams manage security incidents more efficiently. 


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Blackbird’s launch of RAV3N Copilot highlights how generative AI can be a positive for a security team if it’s used to augment contextual information around threats targeting data assets. After all, the faster analysts can understand the cause and impact of a breach, the quicker they can respond. 

Context: The value of generative AI for security teams 

The announcement comes as more and more technology vendors are looking to generative AI to automate security operations. 

For instance, last month Orca Security became the first cloud security company to offer a ChatGPT integration. Under this approach, the vendor uses ChatGPT to process alerts, note the compromised assets and attack vectors and generate instructions on how to remediate the issue. 

Similarly, open-source security provider ARMO also recently released its own ChatGPT integration for the ARMO platform. The integration enables users to create custom Kubernetes controls based on its Open Policy Agent (OPA) with natural language, so they can secure clusters without knowledge of the repo programming language. 

Each of the use cases established by Blackbird, Orca Security, and ARMO highlight how using generative AI to enhance an analyst’s contextual understanding of security incidents or tasks in the SOC, can act as a force multiplier. With RAV3N Copilot, the core focus is on enhancing visibility over risk. 

“Traditionally, risk analysts spend countless hours each month attempting to prioritize the most crucial online risks for their teams or clients,” said Wasim Khaled, cofounder and CEO of Blackbird AI. 

“Legacy solutions often fail to recognize emerging threat patterns and instead rely on simplistic approaches such as keyword counting and sentiment analysis. As a result, analysts are faced with reading through hundreds of thousands of words per day and spend hundreds of hours per week on this task alone,” Khaled said. 

Using Blackbird’s Constellation Risk Engine, RAV3N Copilot aims to remedy this by decreasing the user’s workload so they can more quickly develop insights into risks throughout their environments in real time. Remediation guidance then helps to respond more effectively during live security incidents. 

Blackbird AI’s place in the risk management market 

At a high level, RAV3N Copilot falls within the risk management market, which researchers valued at $31.3 billion in 2021, and estimate will reach $35 billion by 2029. 

While more and more organizations are experimenting with generative AI, Khaled claims RAV3N Copilot is unique in the market. 

“Our technology is a patent-pending innovation that is the first of its kind in the market,” Khaled said. “While others may start summarizing content using large language models, it’s important to note that the whole is greater than the sum of its parts.” 

However, there are parallels between Blackbird and risk management vendors like Dataminr, which is currently valued at $4.1 billion, and uses deep learning–based AI fusion methods to detect security events. Dataminr’s approach leverages deep learning to help organizations detect, prioritize and respond to incidents faster. 

However, Khaled points to Blackbird’s AI-driven narrative and risk engine — the Constellation Risk Engine — as the key differentiator from other risk management products, as it filters data taken to identify custom risks in a way that a more general large language model couldn’t. 

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