What is an attack surface?
An attack surface is refers to all the potential entry points an attacker could exploit to gain unauthorized access to a system, network, or data. Because an attack vector can be any way or method a threat actor uses to illegally access an enterprise’s IT infrastructure, the more attack vectors an enterprise’s IT environment features, the broader its attack surface is.
There are three types of attack surfaces:
physical
digital
social engineering
An enterprise’s physical attack surface includes hardware like computers, mobile devices, external storage drives, laptops, and IoT machinery. The physical attack surface can be exploited via insider attacks, stolen equipment, poor disposal of decommissioned hardware, negligence from remote teams, and many other dangerous scenarios.
The social engineering attack surface specifically refers to the human element, including the susceptibility of individuals within an organization to manipulation and deception. Unlike physical and digital vulnerabilities, which often involve exploiting technical weaknesses in systems, social engineering attacks capitalize on human emotions, cognitive biases, and lack of awareness to trick users into compromising security.
The digital attack surface, on the other hand, poses more complex risks because of the global adoption of cloud computing technologies. The digital or cloud attack surface includes misconfigurations, poor IAM (identity access management), publicly exposed resources, and unofficially commissioned resources (known as shadow IT).
The vast majority of data breaches exploit organizations’ cloud attack surfaces. In fact, only 18% of data breaches in 2023 targeted data outside cloud environments.
What are the components of a cloud attack surface?
Application program interfaces (APIs)
APIs are software that act as connective tissue between multiple heterogeneous cloud applications. They’re the secret to the seamlessness of cloud environments. Unsecured and unencrypted APIs are a significant contributor to an enterprise’s attack surface. One example: In 2023, an API vulnerability in Honda’s e-commerce platform resulted in compromised customer data, dealer records, and other sensitive documents.
Third-party applications
Enterprises expand their attack surface by commissioning third-party applications and tools. These applications include media players, web browsers, and collaboration and communication tools. Today, the high volume of third-party applications is an unavoidable aspect of cloud computing. However, failure to secure these applications can result in a proliferating attack surface.
Gartner predicts that 6 out of 10 supply chain companies will cite cloud-based digital vulnerabilities as a reason for not commissioning third-party vendors in the next two years. While this may seem like a reasonable security precaution, it comes with significant implications, including losing out on potentially transformative services provided by third-party vendors. Instead of eliminating third-party collaboration, businesses should instead acknowledge the inherent risks of third-party applications and mitigate them.
What is API security?
API security encompasses the strategies, procedures, and solutions employed to defend APIs against threats, vulnerabilities, and unauthorized intrusion.
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Databases and storage buckets
Businesses leverage storage solutions from cloud service providers (CSPs) to warehouse their data. Although data storage is quick and convenient with these solutions, there are security implications to consider. For instance, companies need to clearly delineate which security responsibilities belong to them and which belong to their CSPs. Whenever businesses fail to do this, it can result in catastrophic security events. For example, misconfigured and publicly exposed storage buckets can quickly lead to a data breach.
Data
Almost all exploits of an enterprise's attack surface aim to exfiltrate data. Securing data storage containers is insufficient. The data itself needs protection to minimize the attack surface. Some common techniques to protect the data layer in an attack surface include encryption, role-based access controls (RBAC), and backups.
Containers and container management platforms
Containers and container orchestration systems like Kubernetes are becoming widespread in modern cloud-based IT environments. The rise in container culture introduces many deeply embedded risks in infrastructure-as-code (IaC) files in Dockerfiles, Kubernetes YAML manifests, and Helm charts. Container environments bring numerous benefits but can add to an enterprise’s attack surface if left unchecked.
What is Container Security?
Container security is the process of securing the container pipeline, the content running inside the containers, and the infrastructure on which the containers run.
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Users
It’s easy to focus on the intricacies of cloud topologies and forget who is navigating these spaces. Users or “digital identities,” both human and machine, are a dynamic and high-risk component of an enterprise’s attack surface. Over-privileged access and weak passwords and credentials are some of the risks associated with users in cloud environments. Cybercriminals can leverage these risks to move laterally within a business's IT environment, exfiltrate data, and corrupt internal systems.
Code repositories
The rise in high-octane DevOps environments has added to enterprise attack surfaces. Code repositories are potential vectors for threat actors to exploit. This could be due to security flaws, shadow code, and secret or sensitive code. It could also be because of accidentally published early-iteration code in public repositories. Furthermore, companies that haven’t integrated security early in their software development life cycles (SDLCs) are likely to have a much broader attack surface to reckon with.
Artificial intelligence (AI)
AI is a more recent addition to cloud-based attack surfaces. Companies are increasingly leveraging AI tools to augment their cloud operations. While AI can catalyze processes and drive efficiency, it can also pose significant security risks. This makes AI pipelines and tools (including shadow AI) a vector to kickstart major attack campaigns.
In June 2023, our research team discovered that Microsoft accidentally exposed 38TB of sensitive data when their AI researchers shared information using SAS tokens, which enable data sharing between Azure accounts. In addition to open-source AI training data, the researchers accidentally leaked private files. This incident reflects one of the numerous security risks likely to affect organizations’ AI pipelines in the coming years.
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What is attack surface management?
Attack surface management is a combination of tools, processes, and practices that assess, analyze, and remediate potential vulnerabilities across an organization's attack surface. Attack surface management adopts an outside-in vantage point to understand how threat actors might leverage weak spots in an organization's attack surface to conduct malicious activity.
This third-party perspective is vital because it's almost impossible to construct optimal defenses without knowing which perimeter threat actors want to breach, how they plan on doing so, and what they intend to do once they are within the enterprise's cloud environment.
A typical attack surface management life cycle, which we will explore in greater detail in the next section, comprises three steps: attack surface analysis, attack surface monitoring, and attack surface reduction.
Attack surface analysis involves mapping the components of an attack surface like APIs, third-party resources, storage buckets, data, containers, digital identities, code repositories, and AI tools. During attack surface analysis, it's essential to get an interconnected and holistic view of these various cloud assets. Attack surface monitoring involves the constant and continuous surveillance of these assets. Robust monitoring also includes high-level surveillance as well as dedicated and segmented surveillance for specific branches of an organization.
Attack surface reduction focuses on removing as many potential entryways for threat actors as possible. Some key attack surface reduction strategies and practices include right-sizing entitlements for human and machine digital identities, revising security controls, optimizing API configurations, introducing firewalls, and protecting hardware and endpoints with zero-trust fortification.
Attack surface management shouldn’t be periodic. Instead, it should be a constant, continuous, and cyclical process: Analyze, monitor, reduce, repeat. Staying vigilant about attack surface management is especially important because threat actors don’t use the same tools and tactics to breach your defenses. They are constantly innovating to find new ways to sidestep your fortifications. That’s why dormant attack surface management is a security risk in itself. On the other hand, a vibrant, thriving, and innovative attack surface management ecosystem will result in fewer breaches and a minimized attack surface.
The Cloud Security Model Cheat Sheet
Cloud development requires a new security workflow to address the unique challenges of the cloud and to effectively protect cloud environments. Explore Wiz’s 4-step cheat sheet for a practical guide to transforming security teams, processes, and tools to support cloud development.
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A few simple steps to managing your attack surface
Step 1: Analyze the attack surface
Companies can’t protect themselves from danger unless they know what to protect. Therefore, the first step in attack surface management is to identify, add up, and analyze cloud assets to understand the scope and scale of their attack surface. This step essentially involves taking stock of numerous attack vectors, typically a multitude of IaaS, PaaS, and SaaS services, and prioritizing risk. In this step, every aspect and every layer of your cloud environment needs analyzing.
Step 2: Monitor the attack surface
After mapping out and summing up your attack vectors, it’s time to monitor your entire ecosystem to check whether your attack surface is under attack. Examples of tools and strategies to leverage during this step include activity logging, continuous vulnerability scanning, risk-based prioritization, data safety confirmation, and third-party resource assessments. Businesses should also weigh the balance between operational efficiency and robust security to determine risk appetite.
Step 3: Reduce the attack surface
Once you’ve analyzed your attack surface and are constantly monitoring activities, you’ll know where and how to minimize risk. Some effective strategies to reduce your attack surface include decommissioning dormant or redundant users, applications, and resources, and adopting zero-trust concepts like least privilege, just-in-time (JIT) access, and multi-factor authentication (MFA). Businesses should also segment and isolate their networks, train personnel to follow security best practices, encrypt static and in-flow data, and patch vulnerabilities.
Keep in mind that many organizations around the world are paying heed to the importance of zero trust in attack surface management. According to Gartner, 1 out of every 10 large enterprises will feature a fully matured zero-trust program by 2026.
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How Wiz can help you monitor, analyze, and reduce your attack surface
As we’ve seen, a comprehensive attack surface management life cycle has three steps: analysis, monitoring, and reduction. These steps can be incredibly challenging to optimize with siloed tools and legacy security approaches. Wiz’s security solution can help you manage your attack surface at a speed and level of efficiency that can outpace the tools and tactics of threat actors.
Get a demo now to see how Wiz can help you reduce your attack surface, fortify your cloud environments, and accelerate digital success.
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