Top Five Hidden Dangers in AI that Enterprises Must Address
Rajnish Gupta is a seasoned sales leader with over two decades of experience driving cybersecurity growth across global markets. Known for his strategic mindset, people-centric leadership, and deep technological expertise, he champions innovation, customer trust, and continuous learning in the ever-evolving digital security landscape.
In this article, Rajnish highlights the urgent need to secure AI adoption through proactive exposure management and strong governance to protect data and ensure safe innovation.
Organizations are rapidly adopting AI tools like ChatGPT and Microsoft Copilot to unlock unprecedented productivity. However, this sprint towards innovation comes with significant cybersecurity risks. As businesses embrace AI, they create new, often invisible, challenges for their security teams.
This isn't a theoretical problem, a recent Tenable report reveals that 34% of organizations using AI workloads have already experienced a security breach. Despite this clear and present danger, security strategies are failing to keep pace, leaving businesses exposed to several critical risks.
1. The Wild West of shadow AI
Employees are already using personal and unvetted AI tools at work. In just the past two years, the percentage of employees globally who say they have used AI in their role has nearly doubled, from 21% to 40%. Security teams often have no visibility into who is using these platforms or what corporate data is being fed into them.
This proliferation of unapproved AI tools, from open-source models to subscription services, creates a massive blind spot across the network. Without a solution for comprehensive AI discovery, most organizations are flying blind. As the saying goes, you can’t protect what you can’t see.
2. Data leaks and the ‘garbage in, garbage out’ problem
Employees may use AI tools to summarize a report or analyze data, but in doing so, they can unknowingly expose sensitive information like PII, financial details, or proprietary code. Traditional security tools are not designed to monitor this new data flow, making it a nightmare to prevent sensitive information from walking out the digital door.
Compounding the issue, many cloud AI workloads have inherent vulnerabilities and weak data governance. Organizations must be able to track data inputs like prompts and training sets, identify where that data is stored, and determine how AI-generated outputs could leak secrets or enable inference attacks.
AI security cannot be an add-on, it must be woven into the implementation journey from the very beginning.
3. Misconfigurations are an open invitation to hackers
In the race to deploy AI, security can become an afterthought. A simple misconfiguration can be the golden ticket an attacker needs to infiltrate your environment. This could be anything from using default credentials to granting employees excessive access permissions. The Tenable study found that many AI services ship with risky defaults, such as overprivileged service accounts.
For instance, a staggering 77% of organizations using Google Cloud’s Vertex AI Workbench have at least one notebook with the default, overly privileged Compute Engine service account. Organizations need advanced solutions that automatically find and flag these misconfigurations before adversaries can exploit them.
4. Avoiding the Trojan Horse of unsecured third-parties
AI platforms don’t operate in isolation. They are often integrated with a complex ecosystem of plugins, browser extensions, and other third-party tools. Each of these integrations is a potential vector of attack, bringing with it the risk of weak security, hidden vulnerabilities, or unsafe data handling practices.
Like a digital Trojan horse, an unvetted third-party tool can grant unnecessary access, leak credentials, or open a channel for malicious actors to inject harmful code or prompts into your AI workflows.
5. Avoiding prompt injection and jailbreaks
AI has ushered in a new class of threats that don’t rely on traditional malware. Attacks like prompt injection and jailbreaking manipulate an AI model’s behavior through clever, deceptive language. A prompt injection is like a hacker whispering a secret command to the AI, tricking it into ignoring its original instructions.
A jailbreak is a similar technique used to bypass a model's safety and ethical guardrails, coercing it into generating harmful content or revealing sensitive data. These techniques pose a significant threat because even the most advanced models are not immune, making this a critical attack vector to mitigate.
Also Read: How Cyber Defenders Are Using AI to Beat AI
Securing AI beyond the basics
AI security cannot be an add-on, it must be woven into the implementation journey from the very beginning. With security strategies lagging behind adoption, CISOs need to shift from a reactive posture to a proactive exposure management approach. An end-to-end platform is essential for discovering the entire AI footprint, managing the associated risks, and governing its use according to corporate policy.
Such a platform should address the entire lifecycle of AI security. It must provide the ability to find all approved and unapproved AI software, libraries, and plugins to mitigate risks of exploitation and data leakage. A modern exposure management solution with AI Security Posture Management (AI-SPM) is crucial for identifying and prioritizing risks from sensitive data exposure, misconfigurations, and unsafe integrations.
It helps enforce guardrails and organizational policies to control how AI is used, preventing risky user behavior and mitigating novel threats like prompt injection and jailbreaking.
Looking Ahead
The AI revolution is a double-edged sword, capable of creating immense value or introducing complex dangers. To harness its power safely, organizations must be proactive. The goal is to have a security strategy that provides full visibility into the AI attack surface, manages all exposures, and enforces strong governance.
By addressing these critical risks head-on, businesses can protect their data, secure their AI investments, and confidently innovate.
