A stunning 98% of IT specialists think that various AI models are crucial to a company’s performance, according to a recent AI Threat Landscape Report from cybersecurity startup HiddenLayer.
According to a recent AI Threat Landscape Report from cybersecurity company HiddenLayer, a startling 98% of IT experts believe that different AI models are essential to business success. Attackers with financial or other motivations are aware that businesses rely on artificial intelligence (AI) and are working to find ways to take advantage of this. HiddenLayer’s head of threat intelligence, Chloé Messdaghi.
At the Black Hat conference in Las Vegas, Messdaghi clarified, “We’re playing a little game of catch-up.” There is a gray area in an organization’s security posture since not all Chief Information Security Officers (CISOs) are aware of artificial intelligence (AI), even though most businesses use it to manage their everyday operations. For instance, Messdaghi described a situation in which the cybersecurity chief of a corporation was not aware that the business uses close to two thousand different AI model versions. Attackers have created a variety of methods to use AI for nefarious purposes in the interim. One way that malevolent actors can target AI systems is through data poisoning, model evasion, or model theft attacks. Their goals can range from stealing intellectual property to impeding the progress of rival companies.
There are many instances of businesses using AI to outperform rivals, even if generative AI has only been at the forefront for a few years. For example, ChatGPT’s application programming interface (API) was used by TikTok’s owner, ByteDance, to create its LLM, known as Project Seed. Malicious actors, such as financially driven cybercriminals, may also use code injection or prompt injection attacks to target generative AI filters. They may even use supply chain attacks to pervert AI artifacts through the use of code execution, malware delivery, and lateral movement. The potential hazard of interfering with an AI mode that directs a self-driving car is easily imagined. But according to Messdaghi, businesses in the financial, healthcare, and military sectors stand to lose the most if their AI models are used against them.
Malicious actors, such as financially driven cybercriminals, may also use code injection or prompt injection attacks to target generative AI filters. They may even use supply chain attacks to pervert AI artifacts through the use of code execution, malware delivery, and lateral movement. The potential hazard of interfering with an AI mode that directs a self-driving car is easily imagined. But if AI models turn against their owners, Messdaghi claims that the industries most at risk are healthcare, defense, and finance. For instance, deliberate bias or corruption in the loan approval process could have detrimental effects on the economy and society.
Similarly, if hackers manage to access military-grade AI-powered drone systems, terrible things could happen. “Theoretically, there might be situations in which someone might access someone else’s model, such as one that is used to steer drones. And that might be really frightening. even deadly,” Messdaghi clarified. As more businesses take advantage of AI models’ advantages, Messdaghi anticipates a sharp rise in hostile attacks directed at AI. Attackers seldom pass up the chance to use a vector to target businesses, and even fewer of them are aware that it can be used against them.
In the meantime, companies must adjust to the changing threat landscape if they hope to safeguard their customers and end users. According to Messdaghi, identifying AI-based exposure, actively putting red team training into practice, looking for differences in AI output, and enhancing communication between data scientists, engineers, and security teams are the first steps.
Also read: Achieving Rapid Outcomes with AI-Driven Cloud Analytics
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