Recent news reports indicate that nation-state backed actors have taken active steps to compromise Internet of Things (IoT) security cameras. Researchers have found that attackers have targeted a variety of consumer and commercial cameras with widely documented, well-known exploits.
While these types of attacks aren’t new, they highlight the continued risk associated with unpatched and unmanaged IoT devices. These systems are valid targets for public, private, and government organizations. Ignoring this threat could expose your organization to visual reconnaissance and exfiltration that could go undetected by conventional security tools.
Organizations use IoT cameras for physical perimeter security, remote site monitoring, manufacturing quality control, access validation, and much more. In other words, they have visibility throughout your entire environment. At the same time, these eyes into the enterprise often come with fully embedded operating systems capable of functionality outside of their main purpose of camera-based operations. With those extended features, cyber threat actors can co-opt operating systems cto support complex attacks, including:
While IoT-connected cameras may seem like a small factor for network security, they can introduce significant risk if left unpatched. Threat actors fully understand this, and it is important that security teams address the risk.
Cyber-attacks that breach IoT cameras can have far-reaching consequences, such as:
It’s equally imperative to understand how simple remediation is, in theory. In the case of the latest attacks mentioned in the intro, the vulnerabilities had existing patches. One of those patches was close to six years old. These fixes didn’t require advanced IT or security knowledge to apply, just a firmware update.
You might be wondering … if the fixes are readily available for cameras, why don’t teams patch them?
Patching individual devices on a small scale is as simple as installing a firmware patch on each device. However, patching at scale is far more challenging, especially in diverse or expansive enterprise or government environments.
As networks become more distributed, managing IoT systems quickly overwhelms security teams — many of which have limited IoT security tools or expertise. While some systems may come with centralized management platforms, many devices lack this functionality, creating large groups of “unmanageable” systems. This reality is exacerbated by the fact that:
And all of this is made even more challenging as many of the traditional Intrusion and Detection Systems (IDS), Intrusion Prevention Systems (IPS), and network monitoring solutions are not built with IoT in mind. These tools may misclassify devices, fail to detect them, or offer no support at all.
These challenges compound, creating a difficult path forward for organizations looking to improve their IoT camera security.
Effective IoT camera security starts with maintaining a clear and current inventory of all deployed camera devices, their locations, and their exposure levels. Without full visibility, security and IT teams may overlook internet-facing or otherwise high-risk cameras, leaving them unpatched or misconfigured. Even with existing documentation, you should perform regular discovery to identify unmanaged or newly introduced cameras. Shadow IT, such as employee-installed webcams or monitoring devices, can quickly expand the attack surface and create critical blind spots, despite security team’s best efforts.
Beyond inventory, secure deployment architecture is critical. As traditional endpoints become more hardened, threat actors increasingly target IoT cameras as alternative endpoints within enterprise networks. In one reported case, a ransomware group exploited a network camera within a private environment to bypass endpoint detection controls. Even when configured with internal-only access, these systems still pose a significant risk. This exploited camera highlights how threat actors leverage poor segmentation and lax device security.
While patching remains important, many IoT cameras also suffer from inconsistent support for modern security controls such as centralized credential management or secrets vault integration. Weak or unmanaged credentials, combined with poor network segmentation, can leave these devices exposed even when fully up to date.
Whether you already have cameras in use or are getting ready to deploy new systems, a targeted IoT assessments of cameras can significantly decrease risk. Focused testing can uncover device-specific vulnerabilities and gaps in network segmentation and monitoring that traditional security assessments may miss. Given the unique behaviors and access patterns of IoT cameras, specialized evaluation is essential to fully understand and reduce your organization’s attack surface.
IoT camera security may be complex, but it is manageable with the right approach. By combining strong asset visibility, secure network design, continuous monitoring, and targeted testing, you can significantly reduce the risk these devices introduce.
The key is taking a proactive, security-first approach, both before and after deployment. Understanding where cameras are deployed, how they’re connected, and how they’re managed allows you to make informed, risk-based decisions that strengthen overall security posture and avoid breaches that result from unpatched devices.
If you are looking to improve IoT camera security, a specialized IoT security assessment from GuidePoint Security can provide critical insight into device exposure, segmentation gaps, and real-world attack paths that traditional testing often misses.
To learn how to identify and reduce risk across your IoT camera environment, download our IoT Security Assessments datasheet.
Austin Turecek
Austin Turecek is an penetration tester with a focus on IoT, embedded systems, and application security. In the past Austin has worked within incident response, purple teaming, and system administration roles. Prior to beginning his work as an IoT and application penetration tester, Austin worked as a malware analyst studying and tracking cyber criminals, and their tools, throughout the deep and dark web. These combined experiences have all lent themselves to help support the diverse testing focuses required for IoT testing.