TwineToday, you’d have a hard time finding a business leader without at least a passing understanding of the implications of AI. However, far more decision-makers remain fixated on how AI can transform their business processes than on the threats it poses. That blind spot can haunt their organizations. That’s because attackers are already using AI to supercharge their efforts to bypass access controls, steal business data, and otherwise wreak havoc. The AI-powered tools businesses are adopting also carry risks of their own. With that in mind, here are some of the current AI security risks every business should understand.
Risk 1: A much larger identity attack surface
One of the key ways businesses are already leveraging AI is to automate processes by creating new “digital workers.” As they do, however, many lose sight of the fact that those workers can be just as vulnerable to identity theft as human employees. They can also be vulnerable to misconfiguration, exploitation, and overprivileging.
A lack of visibility is another security challenge posed by AI agents. Unlike human workers, they’re out of sight and won’t necessarily check in if they suspect a problem. So, if an attacker successfully exploits an AI agent, they may have unfettered access to company data for some time before anyone notices.
The key takeaway is that shifting to identity-first security is now essential. It’s the only way to guard against the security exposure that comes with rapidly expanding numbers of AI agent identities. It ensures there’s continuous verification and tight permission controls to block attacks on vulnerable AI systems.
Risk 2: AI-powered social engineering at scale
By now, it should be obvious that social engineering attacks like phishing are a primary threat to every business. That’s why employee cybersecurity education has long been a focus. The idea is that an informed employee can spot awkward phrasing, tone, and grammar in a phishing attempt. Unfortunately, AI is making those red flags obsolete.
Already, attackers are using AI tools to generate personalized phishing messages with far fewer obvious tells. Worse, AI lets attackers do this at a speed and scale that was previously impossible. That means employees now see far more phishing attempts that are harder and harder to detect.
Paradoxically, the only viable solution to the problem is an AI-powered anti-phishing system. Only AI moves fast enough and is adaptable enough to scan for AI-generated phishing emails at scale. Fortunately, these systems also eliminate spam and other unwanted messages, so they’re well worth the adoption cost.
Risk 3: Prompt injection data leaks
Right now, AI chatbots and related systems have a peculiar weakness. They’re designed to do whatever they can to satisfy the person using them. On the surface, that sounds ideal. However, it makes them vulnerable to something called a prompt injection attack. It describes a scenario when an attacker uses a carefully crafted prompt to trick an AI system into performing a restricted action. In practice, it can mean accessing protected systems or divulging sensitive data.
The most frightening aspect of prompt injection attacks is how easy they are to execute. An attacker needs no hacking skills. They just need access to an AI prompt, a little ingenuity, and some patience. And worst of all, there aren’t many ways to prevent prompt injection attempts on public-facing AI interfaces.
Right now, the safest thing businesses can do is to draw a hard line between internal and external AI systems. The former should have strict usage controls and logging, and the latter should have no access to sensitive data whatsoever. That way, an attacker has nothing to talk an agent into divulging.
Risk 4: Malware-free and identity-based attacks
For years now, malware has been the go-to method hackers used to gain a foothold inside business networks. Today, AI lets attackers skip malware altogether in favor of mass identity-compromise attacks. It makes it faster and easier to automate defense probing and permission-structure analysis, and to find a viable path into protected systems. These attacks also evade most business antivirus and antimalware systems, making successful breaches much harder to detect.
The solution is for businesses to move to next-generation antivirus solutions. They rely less on signature-based detection and more on continually updated pattern detection. In other words, they don’t look for static hallmarks of an attack. Instead, they monitor for unusual activity relative to established baselines.
For example, imagine an attacker gains access to a mid-level employee’s user credentials. If that account suddenly begins accessing data it typically wouldn’t, or interacting with new systems, a next-gen antivirus would notice. Then it can lock out the user pending investigation or initiate surveillance, depending on the organization’s security posture. Such solutions also do well at detecting employee malfeasance. Since insider threats are another major risk for most businesses, next-gen antivirus solutions are a must-have.
AI is now a business issue, not just a technical challenge
The bottom line is that business leaders must wake up to the threat that AI adoption poses to their cybersecurity. Meanwhile, they must also recognize that attackers are arming themselves with AI tools that outclass traditional cybersecurity measures. To contend with this new threat landscape, organizations must put AI security at the core of future cybersecurity efforts. Those that act early should stand the best chance of evading an ever-growing wave of new threats. Those that don’t may find that their rush to AI adoption has far more costs than they ever considered.
Vicky
