10 Container Vulnerability Scanning Tools in 2025

Containers revolutionized the way software is deployed, but a misconfigured image or a vulnerable library can be dangerous. A report reveals that 87% of container images in production have high-severity vulnerabilities, up from 75% of containers in production in the previous year. Ongoing scanning is crucial to identify such vulnerabilities and ensure that they are not exploited in containerized environments. So, let us discuss container vulnerability scanning tools, how they work, ways to use them, and how to maintain secure container deployment.

This article explains how container vulnerability scanning tools work in order to identify containers with unpatched software or code vulnerabilities. We will introduce the concept of container image vulnerability scanning tools and clarify the significance of advanced scanning solutions. You will learn about container vulnerability scanning best practices that unify DevOps speed with robust security. We will highlight vulnerability scanning containers from build time to runtime, ensuring ephemeral workloads remain properly inspected. Finally, we will detail ten leading container scanning tools, including SentinelOne, focusing on their features, roles, and critical advantages for 2025.

What is Container Vulnerability Scanning?

Container vulnerability scanning is the process of identifying security risks in container images and their dependencies, including outdated or malicious packages and misconfigurations. It may involve examining Dockerfiles to identify security issues, inspecting base OS layers, and comparing code dependencies to CVE databases. By adopting types of vulnerability scanning tools that are tailored specifically to containers, dev teams can detect threats before shipping images into production. Some pipelines incorporate scanning natively and prevent merges or deployments if critical vulnerabilities are found.

Over time, it scales up to the runtime, checking that the instances of the ephemeral containers do not contain newly discovered vulnerabilities. In the long run, this approach is consistent with broad container vulnerability management objectives – achieving safer and more secure container environments.

Need for Container Vulnerability Scanning Tools

A Statistics reveal that 80% of organizations reported that they have suffered from some form of cloud security incident in the past year. While containers drive microservices in these cloud environments, vulnerabilities can be exploited through scanning gaps. Container vulnerability scanning tools proactively scan containers for vulnerabilities to avoid DevOps introducing exploitable code. Here, we outline five reasons why these tools are especially critical in container-based environments:

1. Preventing Zero-Day Exploit Windows: Whenever CVEs for major libraries or frameworks are released, attackers immediately start exploiting them against the container images present in public repositories. With scanning tools that monitor CVE feeds in real-time, dev teams fix vulnerabilities before cybercriminals exploit them. This synergy helps to maintain low levels of container downtime. As transient computing environments are created and destroyed, it scans for cases where outdated packages containing known exploits are being used.
2. Handling Multi-Stage Builds: Many Dockerfiles use multi-stage builds where the runtime image is small, but build stages can contain stale dependencies. Basic scanning might not scan through the intermediate layers. Container vulnerability scanning tools that perform deep-layer scans expose residual flaws. In the long-run, it is useful to make certain that every stage is thoroughly checked to avoid having partial solutions becoming part of production images.
3. Improving Compliance Posture: Organizations that fall under PCI-DSS, HIPAA, or data privacy laws must prove compliance with patching and scanning. These audits are simplified by tools, which produce logs of discovered issues, fix timelines, and final confirmation. In this way, through documentation of scanning events in a certain pipeline, teams are able to demonstrate compliance as and when it is needed. This approach helps in building brand trust and also satisfies external governance standards.
4. Streamlining DevOps Collaboration: Some development teams are reluctant to employ security checks if these slow down the release rate. However, integrated scanning that surfaces the flaws early helps in the development of the security-as-code mindset. It gives back simple, automated feedback to developers to help them correct the code before it gets integrated into the main branches. As time passes, scanning is no longer an isolated security activity but is integrated into the development processes.
5. Reducing Overall Security Costs: Fixing issues in containers after they have been deployed could sometimes mean significant restructuring or lead to system outages. When identified at the pipeline stage, teams address issues for a relatively low cost and within a short time. This early fix mentality also prevents the occurrence of further incidents that would lead to other breaches, which are otherwise costly in terms of incident handling. Adopting consistent scanning, on the other hand, makes a lot of sense because patching is done proactively without having to wait for a crisis under pressure from the attacker.

Container Vulnerability Scanning Tools in 2025

As we move ahead in 2025, many solutions claim to be able to identify container-based vulnerabilities in various frameworks. Below, we have listed ten container vulnerability scanning tools that assist the DevOps teams in keeping the images secure. All of them have different scanning features, integration possibilities, or AI-based analysis. Here, we give brief descriptions along with basic specifications to help your decision-making:

1) SentinelOne Singularity™ Cloud Security

SentinelOne Singularity™ Cloud Security platform provides CNAPP protection in cloud workloads across build time and runtime. It provides full support for VM, serverless, and container-based resource scanning. Through the integration of advanced analytics with local AI engines, it scans for weaknesses and provides solutions. DevOps teams get a single view into containers whether they are on public or private clouds, eliminating guesswork in patch cycles.

Platform at a Glance:

1. Unified Architecture: SentinelOne Singularity™ extends scanning to container image layers, orchestrators, and run-time states. It also supports multi-cloud footprints as well as on-premises infrastructure from a single management console. Local AI detection reduces the time taken between the identification of the vulnerability and the time it takes to address it. This makes patch orchestration for these transient workloads more manageable and efficient.
2. Real-Time Response: Through the use of threat intelligence, the platform is capable of blocking potentially malicious container behavior on its own. Identified exploit paths help to determine which vulnerabilities pose a threat in the immediate future. This is ideal for short-lived applications such as microservices that can be easily scaled up or down. The integration of scanning with real-time blocking results in a continuous protection mechanism.
3. Hyper Automation: Automation capabilities allow the DevOps teams to integrate scanning events into the build process. If critical flaws are discovered, the pipeline may stop the release or automatically deploy a base image with security patches. This synergy ensures consistent alignment with container vulnerability scanning best practices, removing human error from routine tasks. In the long run, partial or full automation leads to efficient and timely rectification of the issue.

Features:

1. AI-Powered Analytics: Detects any forms of anomalies within the container images or code packages.
2. Compliance Management: The logs and dashboards identify vulnerabilities and correlate them with PCI-DSS or other standards.
3. Secret Scanning: Detects leftover credentials or tokens in container layers.
4. Graph-Based Inventory: Describes the relationships between containers, which makes it easier to prioritize and apply patches.
5. Build-time & Runtime Agents: Scanning at build time as well as at runtime using local logic support.

Core Problems that SentinelOne Eliminates:

1. Overlooked ephemeral containers that skip scanning.
2. Tedious manual patch processes slowing DevOps releases.
3. Reintroduction of older flawed images in multi-cloud registries.
4. Gaps in threat detection, especially for zero-day or new vulnerabilities.

Testimonials:

“Singularity Cloud Workload Security provides us with better security detection and more visibility. It is another resource that we can use to detect vulnerabilities in our company’s systems. For example, it can help us detect new file processes that we are not familiar with, which could be used by attackers to exploit our systems. Singularity Cloud Workload Security can also help us diagnose and analyze data to determine whether it is malicious or not. Singularity Cloud Workload Security is like another pair of eyes that can help us protect our systems from cyberattacks.”

• Phat Pham (Cyber Security Analyst)

See how users rate SentinelOne for container vulnerability scanning on Gartner Peer Insights and Peerspot. 

2) Snyk Container

Snyk scans container images for known vulnerabilities in libraries that have been used in building the image. It integrates with Git repositories, CI/CD pipelines, or container registries. Additionally, it offers the suggested mitigation for each of the CVEs that were identified, and can identify old or vulnerable open-source libraries that may be used.

Features:

1. Git Integration: Examines Dockerfiles or container configurations in the source code stage.
2. Automatic Fix Suggestions: Specifies whether there are new versions or patched packages available.
3. Registry Integration: Scan images stored in Docker Hub or any other registry.
4. License Scanner: Looks for license problems in libraries and frameworks.
5. DevOps Pipeline Hooks: If certain vulnerabilities are found, it halts the merges.

Discover what users say about Snyk Container on Peerspot.

3) Aqua Trivy

Aqua Trivy is a tool that scans container images, file systems, or Git repositories for vulnerabilities, including those in the CVE database. It works fast and can provide output in text or JSON format for further integration into a program. The commercial Aqua platform now covers the runtime protection level. It uses vulnerability databases for the constant detection of new threats that may exist in the system.

Features:

1. Scanning: Detects OS packages and library flaws with minimal overhead.
2. Open-Source Data: Pulls CVE information from multiple Linux distributions and languages
3. Configuration Analysis: Highlights problems that may arise in Dockerfiles or Kubernetes deployment files
4. CI Integration: Integrates with scripts to fail builds on critical vulnerabilities
5. Community Support: Gets regular database updates and contributions from contributors.

Learn what rating users have provided to Aqua Trivy on Peerspot.

4) Anchore (Anchore Engine)

Anchore scans the container images for operating system and application-level vulnerabilities. It also includes policy checks meant to filter out images containing prohibited libraries. Anchore Engine is an open-source tool, although paid versions of it exist under the name of Anchore Enterprise. It supports detailed policy compliance with vulnerability assessment features.

Features:

1. Layer-by-Layer Inspection: Determines which layer of the container is responsible for each CVE.
2. Policy-Based Checks: Prevents images from being used if the severity level or licensing standards are not met.
3. CI/CD Integration: Hooks into Jenkins, GitLab, and other platforms for gate checks.
4. Reporting: The discovered issues are reported according to their severity, location, or the package in which they were found.
5. Flexible Deployment: Runs as a standalone service or within container environments.

Check how users review Anchore Engine on Peerspot.

5) Prisma Cloud (Palo Alto Networks)

Prisma Cloud is a cloud security posture management tool, and it also includes container scanning capabilities. It scans images, serverless code, and orchestrator configurations, and provides runtime protection of containerized microservices at runtime. It is available across leading cloud providers with integrated security intelligence.

Features:

1. Multi-Cloud Coverage: Performs scans in AWS, Azure, or GCP environments.
2. Runtime Protection: Monitors the container processes to identify any irregular behaviors.
3. Policy Enforcement: Coordinates the outcomes of scanning with compliance or internal needs.
4. Layered CVE Analysis: Scans each layer of a container image to determine if it contains any known CVEs
5. IAM Oversight: Conducts checks on permissions within the orchestration systems to avoid granting unnecessary permissions.

Find out how users experience Prisma Cloud on Peerspot.

6) Tenable.io Container Security

Tenable.io expands its vulnerability scanning to container images and identifies old OS layers, vulnerable libraries, or misconfigurations. It connects with Docker registries and orchestrators and assigns a risk score to flagged items. It groups containers together with the other IT assets in the same console and provides patch tracking for vulnerabilities that have been discovered.

Features:

1. Risk Analysis: Determines the risk value for the identified vulnerabilities by rating their severity and probability of being exploited.
2. Registry Automation: Scans images from public or private repositories on a schedule.
3. Ecosystem Integration: Connects with Nessus or other Tenable products.
4. Configuration Verification: Identifies errors in Dockerfiles or Kubernetes resource specs.
5. Benchmarks: Compares container setups against known security best practices.

See what users think of Tenable.io Container Security on Peerspot.

7) Clair (CoreOS/Quay)

Clair is an open-source tool that scans through the container image layers and checks for any known CVEs. It logs detected issues into a database and makes the results available through an API. Based on the information provided, Quay, a container registry, can automatically perform scanning through Clair. It also performs static analysis on each image layer with a lower overhead.

Features:

1. Layer Wise Matching: Identifies the specific vulnerabilities introduced at each layer of the Docker.
2. Integration with DevOps: This can be incorporated into custom pipelines or into already existing registries.
3. Integration with Quay: Auto-scan images when new versions are pushed or tagged.
4. Community Updates: Gets updated often with the CVE database.
5. Lightweight: Operates with minimal resource requirements.

Explore how Clair is rated by users on Peerspot.

8) Cortex Cloud (Palo Alto Networks)

Cortex Cloud provides features such as container security scanning, runtime protection, and compliance. This tool supports Docker, Kubernetes, and other serverless platforms. It scans images before they are sent into the running environment and also constantly observes containers that are already running. It also provides patch management and organizational dashboards that offer vulnerability prioritization and remediation with an overview of general security.

Features:

1. Runtime Oversight: Tracks container operations for abnormal behavior.
2. Registry Scanning: Performs scans on images when they are pushed or at a specified time.
3. Compliance Templates: Relates scans to NIST, PCI, and other compliance frameworks.
4. Network Segmentation: Regulates the interactions between containers to prevent the spread of threats within the network.
5. Developer Tools: Provides CLI-based scanning for Dockerfiles or images.

Discover what users share about Cortex Cloud on Peerspot.

9) Sysdig Secure

Sysdig Secure is a solution that has the capability of scanning containers and monitoring the running containers. It analyzes system calls in Kubernetes or Docker environments to identify any malicious behavior while incorporating policy enforcement and the use of policies with suggested resolutions. It combines the features of vulnerability scanning and real-time anomaly detection.

Features:

1. Kubernetes-Aware Scanning: Links image data to pods or services running in the Kubernetes cluster.
2. Syscall-Level Monitoring: Monitors container processes for signs of malicious activity.
3. Policy Enactment: Removes or labels images that are deemed to be violating the security policies.
4. Suggested Fixes: Points to patched libraries or updated configurations.
5. Compliance Mapping: Relates scan outcomes to PCI, HIPAA, or other frameworks.

Learn how users rate Sysdig Secure on Peerspot.

10) NeuVector (SUSE)

NeuVector uses container images for scanning for known CVEs and for inspecting container traffic after the containers have been deployed. It discovers exploitable libraries before the containers are deployed and analyzes the network activity while they are in use. It also implements policies that define what is allowed within each container and is compatible with Docker, Kubernetes, and other orchestration solutions.

Features:

1. Network Interrogation: Looks for symptoms of container traffic on the network
2. Registry Scans: Performs scans at the time when images are pushed to a registry
3. Runtime Visibility: Watches processes and file activity within running containers
4. Policy Controls: Ensures that containers cannot run if they are  violating security policies
5. Orchestrator Integration: Fits into Docker, Kubernetes, and similar platforms

Check out what users say about NeuVector on Peerspot.

Key Considerations for Selecting a Container Vulnerability Scanning Tool

When deciding among these container scanning tools, factors like environment scale, DevOps pipeline design, and unique compliance needs shape your choice. Some of the solutions are designed for small development teams while others are suitable for managing thousands of containers across multi-cloud. In the next section, we outline five key factors to help you select a scan tool that complements your security and development processes.

1. Integration with CI/CD: Real-time detection is best achieved by using a scanning tool that integrates with Jenkins, GitLab, or other pipelines directly. If the pipeline can gate merges when major vulnerabilities are identified, dev teams address them before they go through the pipeline. Lack of integration may lead to patch run-ups towards the end of the development process. In the long run, integrating scanning into development processes makes “fix on commit” the new norm, which eliminates known vulnerabilities from being released.
2. Layer-by-Layer Visibility: Since the images are built in layers and each layer is added gradually, the scanner has to determine which layer introduced the vulnerability. This makes it easier for devs to identify the source of the problem—maybe an outdated library in an instruction that builds a Docker image. Not all scanning solutions are the same, and some of them have issues with multi-stage Dockerfiles. Think about whether the tool could be useful for your layering strategy or your use of specialized base images.
3. Runtime Defense Options: Some scanning tools only verify still images, whereas others use static checks with runtime monitors or intrusion detection and prevent the execution of suspicious processes. When it comes to container vulnerability management, it is helpful to connect image scanning with active runtime protection. By utilizing a single platform that scans and blocks threats in real-time, DevOps pipelines can be aligned with production security.
4. Policy Enforcement and Compliance: If compliance is imperative, then a solution that either generates or enforces policy rules, for instance, no pushing images that have a specific CVE severity level, is valuable. The tools vary in terms of how they correlate the identified issues to frameworks such as PCI-DSS. Select a solution that will generate the logs and the dashboards that are required for audits. In the long run, proper policies help to prevent dev teams from neglecting scanning processes unconsciously.
5. Licensing, Cost, and Scalability: It is also important to note that as the usage of containers increases, the amount of scanning that is required also increases. Some of the tools charge per image or per agent, while others allow for an unlimited number of scans. Consider the costs, especially if you use ephemeral containers in dev, staging, or across multiple production clusters. Also, ensure that the tool can be used across multiple cloud environments without a significant impact on performance.

Conclusion

Container vulnerability scanning tools help DevOps teams and security specialists monitor known vulnerabilities in short-lived containers or microservices. Through the analysis of base layers, code merge scans, and sometimes the verification of runtime states, these tools prevent threats from becoming worse. The nature of containers is transient, and therefore, periodic scanning at the time of build or each image push is appropriate. In the long run, integrating the usage of scanning with automatic patch or rebuild processes contributes to the least amount of exploit time. Moving ahead in the future, effective scanning solutions will be mandatory for organizations that rely on containers to perform their business-critical operations.

However, scanning is not sufficient without a supportive pipeline, clear processes documented for fixing issues, and an organizational culture that embraces the concept of continuous improvement. Organizations that incorporate scanning into DevOps closely and reject merges with vulnerable code see fewer problems in the container. For instance, SentinelOne’s AI analytics integrate scanning, real-time detection, and patching for enhanced coverage. With scanning events combined with swift fixes, organizations reduce the amount of time attackers have access to the network significantly.

Want to take container security efficiency to the next level?  Learn how SentinelOne Singularity™ Cloud Security integrates AI-powered scanning, automated patch management, and dynamic runtime protection for your container environment.