AWS Vulnerability Assessment: An Easy Guide 101

Ensuring the security of cloud environments is now a challenge as companies expand their operations on public clouds. Amazon’s customer base expanded to 4.19 million customers in 2025 (this only includes companies with a physical street address), indicating how much they rely on AWS for their business. More organizations mean an even larger number of targets for potential threats, and as such, more rigorous strategies must be employed to identify threats and prevent them. Without a consistent method for identifying AWS known vulnerabilities, organizations can be blindsided by exploits targeting overlooked configurations or unpatched systems. This scenario makes AWS vulnerability assessment the linchpin of a robust cloud security strategy.

In this article, we will cover:

1. An introduction to AWS vulnerability assessment and why it is so important for any business that is using the cloud.
2. Understanding the importance of vulnerability management in AWS and the factors that make it necessary to have an effective program.
3. A detailed review of common AWS vulnerabilities and the platform’s native security tools, along with their potential limitations.
4. Strategies, measures, and approaches that enhance vulnerability management in AWS within a rapidly changing environment.

What is AWS Vulnerability Assessment?

AWS vulnerability assessment is a structured, ongoing process to identify, assess, and mitigate security gaps in Amazon Web Services environments. This covers scanning cloud configurations, operating system layers analysis, container images review, and high-risk component patching. Teams can embed scanning workflows into DevOps pipelines and daily operations, finding AWS vulnerabilities before threat actors can exploit them. This proactive method ensures that critical vulnerabilities are promptly addressed by correlating identified scanner findings with associated risks. At the same time, an effective plan consists of AWS native solutions and third-party integrations to cover the most. When done right, it supports a strong security posture that balances compliance requirements with operational agility in the cloud.

Why Vulnerability Management Is Critical in AWS Environments?

Businesses leverage cloud computing to transform their application deployment methods, yet the accelerated deployment speed creates novel security risks. Research indicates that over 2,300 distinctive cyberattacks take place daily, with public cloud misconfigurations and unaddressed security patches as primary targets. The complexity of AWS infrastructure, which extends from EC2 through S3, RDS and serverless frameworks, creates multiple AWS known vulnerabilities that can escape detection. Customers must maintain control of operating systems, network rules, and application logic, even though Amazon secures both the hardware fundamentals and hypervisor base. Under this shared model of responsibility, organizations must maintain a comprehensive and continuous method to handle AWS vulnerabilities.

Inadequate attention to vulnerabilities results in major breaches through both misconfigured S3 buckets and unpatched container images. Cloud transformation speed increases exposure risks because new instances and scale operations happen frequently, which creates potential new security threats. In the end, organizations that handle vulnerability management casually face immense financial losses, together with legal troubles and damaged reputations.

Need for AWS Vulnerability Assessment

AWS offers flexible and scalable environments to run workloads, but requires a strong focus on security to keep the environment secure. However, if these steps are not followed by a proper methodology, there are chances that critical vulnerabilities remain undetected. Since the cloud environment evolves rapidly, scanning for AWS known vulnerabilities must keep pace with dynamic provisioning and resource changes. Below, we dive into five key drivers behind the need for a robust AWS vulnerability assessment framework:

1. Continuous Infrastructure Changes: AWS promotes the on-demand usage of resources, which causes the creation and deletion of virtual machines or containers frequently. This makes it easier to achieve agility, but at the same time, it makes it difficult to monitor the process manually. A dedicated approach to AWS vulnerability assessment policy ensures each newly deployed instance undergoes scanning and patch checks. Continuous monitoring is an important aspect to prevent the occurrence of misconfigurations that may occur at some point in time.
2. Shared Responsibility Model: While Amazon controls the physical infrastructure, physical network, and virtualization layer, customers are responsible for OS layers, data, and application stacks. Failing to patch an EC2 instance or mismanaging permissions in an S3 bucket can open the door for breaches. AWS vulnerability assessment best practices revolve around fulfilling this side of the shared responsibility, plugging gaps that Amazon’s protections don’t cover.
3. Regulatory and Compliance Pressures: Many regulations, such as GDPR, PCI DSS, etc., make it mandatory to carry out vulnerability assessments in production environments while in use. In this case, organizations hosting sensitive data on AWS need to demonstrate that they are regularly scanning for vulnerabilities, deploying patches as necessary, and managing risks. A well-crafted AWS vulnerability assessment policy not only meets compliance but can also reduce audits’ complexity and cost.
4. Threat Landscape Evolution: Cyber attackers adapt their approaches, be it through the utilization of more recently disclosed CVEs or the more sophisticated phishing attempts involving cloud credentials. Attackers also research common AWS vulnerabilities in search of simple entry points. Updated scanning signatures and risk analysis in AWS environments are essential to guarantee that discovered flaws are fixed promptly to prevent attacks.
5. Cost of Downtime and Incident Response: A single data breach or resource compromise can lead to extended outages that result in lost revenue and lost reputation. Systematic AWS vulnerability remediation—supported by automated scanning or patch orchestration—lowers the chance of an extended incident. This, in turn, maintains brand credibility and averts the severe financial consequences of extensive security incidents.

Common Vulnerabilities in AWS Infrastructure

While AWS comes with fundamental security measures in place, several mistakes can be made that compromise it. Some of the shortcomings include basic misconfigurations in IAM and extensive misconfigurations in resource policies. Understanding these typical issues helps shape an AWS vulnerability assessment policy that addresses them proactively. Here are some of the most common vulnerabilities in AWS:

1. Misconfigured S3 Buckets: S3 buckets that are exposed to the public are another issue that remains a constant and is often attributed to default configurations or a failure to adhere to best practices. Once these attackers discover these open buckets, they can read or even alter and delete such important information. Automated tools that scan S3 policies can help point out policies that grant open permissions at the get-go. To ensure that the list is up-to-date, frequent re-checks are made, especially in cases of new deployments or changes of ownership.
2. Excessive IAM Privileges: When IAM roles or user accounts have excessive privileges, attackers who obtain the corresponding credentials can move between multiple AWS services. Through the principles of least privilege, teams ensure that each user or service account only has the necessary access level to perform their tasks. This principle stands as an essential part of AWS vulnerability assessment best practices, ensuring that misused credentials don’t wreak havoc.
3. Outdated EC2 AMIs or OS Versions: Using an outdated operating system or an outdated AMI can bring in different types of vulnerabilities. Although AWS offers some basic patching for specific services, it is the user’s responsibility to manage instance patching cycles. Scanning solutions highlight known CVEs in the OS layer, prompting timely AWS vulnerability remediation. This measure helps in preventing the exploitation of vulnerabilities in outdated applications.
4. RDS Configuration Errors: AWS Relational Database Service makes it easy to host databases, but weak networking or identity rules can allow intruders in. This is because exposed endpoints, unencrypted connections, or lack of backups become attractive targets for the exfiltration of data. Ensuring RDS logs and connection policies align with AWS vulnerability assessment policy mitigates such misconfigurations.
5. Insecure Serverless Functions: Lambda functions sometimes require secret credentials or elevated permissions to call other services. If attackers discover code injection flaws or guess environment variables, then they may execute code on the system. Continuous scanning and best practices around ephemeral data storage help prevent these functions from becoming a weak link. Checking for common AWS vulnerabilities within serverless deployments ensures a more robust posture.

Steps to Perform an AWS Vulnerability Assessment

AWS workloads change every minute, creating new instances, services, and serverless functions in a matter of seconds. Security teams, therefore, require a focused pattern that identifies problems fast and is compatible with cloud-native tempo. The sequence outlined below offers an example of a cloud-specific playbook that augments standard vulnerability management procedures. Embrace it to ensure that the organization remains visible, has a small attack surface, and can meet compliance audits.

Step 1: Inventory EC2, S3, Lambda, IAM, and More

AWS APIs or tools such as AWS Config can be used to fetch a real-time list of compute, storage, and identity resources. Information such as instance IDs, security groups, and associated IAM roles should be captured. It is recommended to tag each asset with the environment it belongs to (production or development) as well as the data sensitivity level. Update the inventory either on a periodic basis or as prompted by an event.

Step 2: Scan for OS & Application Vulnerabilities

Perform a scan on the EC2 AMIs, the container images, and the running instances using Amazon Inspector or a third-party tool. Integrate language libraries and runtime packages with the base operating systems. Run tests on the instance automatically as soon as an instance is created in order to detect any problems before going live. Export the results to Security Hub or a SIEM for further analysis and consolidation.

Step 3: Use AWS Config & Security Hub to Assess Configurations

Check S3 bucket ACLs, IAM policies, VPC flow logs, and encryption settings against best‑practice rules. Utilize Config rules or Security Hub standards (CIS, PCI, or Foundational Security) to identify deviations from set standards and benchmarks. Identify misconfigurations that result in making data publicly available or enabling the lateral movement of malicious actors. Enable quick fixes for resource owners by notifying them automatically.

Step 4: Prioritize Risks Using CVSS and Asset Value

Integrate the scanner’s severity ratings with business context factors, including whether an EC2 instance processes customer data or supports revenue-generating functions. Emphasize areas of greatest potential where a specific CVE corresponds to an internet-connected workload. Create reports that will display risks according to account, region, or business unit to support managerial decisions. It is recommended that remediation deadlines be synchronized to the level of exposure.

Step 5: Remediate and Monitor

Use Systems Manager, update CloudFormation templates, or modify IAM policies as required. For serverless functions, build and deploy code packages with updated dependencies. After remediation, perform additional rescans of specific findings to validate the closure and enable GuardDuty or CloudTrail for continuous monitoring. Continuous monitoring makes certain that new resources are configured securely and remain compliant as time goes by.

The Limitations of Native AWS Security Tools

While AWS’s integrated services form a significant starting point for AWS vulnerability assessment, each has constraints that can limit coverage or flexibility. Knowledge of these limitations enables teams to determine when to use built-in tools or integrate third-party or open-source applications. In the following section, we present a summary of the main limitations of each solution.

Amazon Inspector

Amazon Inspector scans EC2 instances for vulnerabilities, but its functionality is limited. It is limited to specific OS images only and relies on frequent updates to the rules governing its operation. Although it is useful for single-out scanning, it might not work well with complex multi-cloud or even container-based environments.

5 Limitations

1. Compared to other, more focused solutions, there is a limited range of containers that can be scanned.
2. Focuses primarily on known CVEs without advanced anomaly detection.
3. It may generate false positives in the case of deviations in the OS baseline from the norm.
4. Provides limited orchestration of patches, which often needs further manual intervention.
5. Lacks direct scanning for common AWS vulnerabilities in serverless or big data services.

AWS Security Hub

Security Hub is a centralized service that consolidates security data from other AWS services and provides an overall risk assessment. This approach aids integration of data but may not achieve the kind of detailed scanning depth that some organizations need. Large-scale environments may also encounter challenges in integrating Security Hub with other specific compliance frameworks.

5 Limitations

1. Does not include detailed vulnerability scanning on its own, but integrates with other AWS services or third-party tools to perform the function.
2. Lacks in-depth patch automation for direct AWS vulnerability remediation.
3. Multi-account structures are not easy to manage, and this can make it difficult to maintain policies across various accounts.
4. Custom rules, therefore, need a lot of fine-tuning to meet the desired level of performance.
5. Lacks direct integration with on-premises or multi-cloud solutions, which does not facilitate collaboration across platforms.

GuardDuty

GuardDuty is effective in real-time threat detection by identifying unusual patterns in logs. However, it is not a complete vulnerability scanner and cannot fix or quarantine these problems on its own. It is more focused on identifying anomalies rather than scanning for missing patches directly.

5 Limitations

1. No direct scanning for AWS known vulnerabilities in OS or application layers.
2. Relies on continuous log ingestion — any interruption in the log feed could potentially leave gaps.
3. Although it provides severity scores for identified anomalies, some businesses find it hard to confirm, which creates challenges in the triage process.
4. Threat intelligence is not very detailed and does not include specific exploits of the actions taken.
5. Lack of integrated patch or reconfiguration workflows for instant problem-solving.

AWS CloudTrail

Amazon CloudTrail tracks and records all API events, making it an invaluable tool for forensics and audit purposes. However, it is not a vulnerability scanner or a patch manager. Most teams depend on third-party tools that help decipher CloudTrail logs against real-time detection or patch orchestration.

5 Limitations

1. It does not actively search for vulnerabilities or misconfigurations in the network.
2. Real-time risk alerts require handoffs to other services or third-party solutions.
3. Forensics can be quite time-consuming, finding an exploit after it has occurred.
4. Lacks features for auto-remediation of the environment or for scheduling patches.
5. In large-scale environments, logs can create significant overhead if not effectively processed.

Amazon Macie

Macie is focused on data classification and potential exposure identification in S3. However, it does not necessarily point out specific code-level weaknesses or system configurations. Organizations that require broader scanning functionality will find that Macie’s data-centric capabilities are limited.

5 Limitations

1. The S3-centric approach leaves out the possibility of scanning for vulnerabilities in EC2, EKS, or RDS.
2. No self-healing or repair mechanism for discovered data leaks.
3. Limited utility outside compliance or data leak scenarios.
4. Real-time detection involves constant scanning of storage buckets at regular intervals.
5. Lacks advanced threat correlation to connect data leaks to attempts at exploitation.

Automating Vulnerability Detection and Remediation of AWS

Due to the limitations of native AWS tools, some organizations apply additional solutions to implement a more effective approach. Automation ranges from pipeline scans in DevOps to patch cycles that are initiated based on severity levels. By adopting a cohesive strategy, teams can swiftly spot and close AWS known vulnerabilities before they become breach vectors. The following are the four main areas of focus.

1. Continuous Integration and Scanning Pipelines: Integrating vulnerability checks into CI/CD processes ensures that newly committed codes are scanned for vulnerabilities. Integration with scanning engines enables problems to be detected at an early stage, and merging halts if critical defects are found. This approach not only fosters AWS vulnerability remediation speed but also ingrains security within developer routines. Newly constructed containers or updated functions in your environment are automatically tested as the environment changes.
2. Automatic Patch Orchestration: While other automation tools only inform on vulnerabilities, the most sophisticated ones also deploy vendor patches or configuration updates. Combined with clear maintenance windows, these solutions deliver changes with limited interruption. Based on the metrics obtained from scanning results, policy logic determines which issues need to be fixed right away. In the long run, it becomes less costly to automate the updates, freeing up personnel to attend to more important activities.
3. Unified Dashboards and Risk Scoring: Security teams have to work with data from different AWS services and third-party scanners. These feeds are integrated into a single dashboard that displays the overall risk profile. The system categorizes vulnerabilities, and the user can easily identify the most critical ones. This synergy clarifies where to direct scarce resources, anchoring a data-driven approach to AWS vulnerability assessment policy enforcement.
4. Real-Time Alerts and Escalations: Automation is not only limited to scanning but also extends to incident notifications. In case newly discovered CVEs or misconfigurations appear, the system notifies the appropriate teams. With integration to chat tools or incident management systems, the process of triage is made easier. This real-time detection and escalation cycle helps to prevent high-impact flaws from remaining dormant in your AWS environment.

Best Practices for Managing Vulnerabilities in AWS Cloud

Even with robust scanning or patching tools, success in AWS vulnerability assessment hinges on well-crafted policies, disciplined routines, and a culture of continuous improvement. Here are four best practices that help to build a solid foundation for vulnerability management, each of which addresses security from a different perspective:

1. Integrate Security and DevOps for a Single View of the Environment: If development and security teams are working in harmony, then there is no conflict around issues such as patch testing or code changes. Both sides stay informed by integrating scanning into CI/CD pipelines and sharing the metrics. This open channel reduces the blame culture and fosters collective ownership of the AWS vulnerability assessment policy. In the long run, developers also improve the scanning logic to identify domain-specific oddities.
2. Enforce Least Privilege Principles: The AWS Identity and Access Management may become complex, especially if the roles and permissions continue to increase. Reducing privileges limits the actions an attacker can perform even when they have compromised one account. Adhering to the principle of least privilege stands among the top AWS vulnerability assessment best practices, limiting lateral movement in compromised scenarios. Periodically, IAM roles should be checked, and those that are no longer needed or those that grant unnecessary permissions should be deleted.
3. Maintain a Dynamic Asset Inventory: Do not expect your environment to remain static, especially if you use auto-scaling or your containers are ephemeral. A real-time, auto-updated inventory makes sure that scanning coverage is not left out in any instance. This living repository underpins an effective approach to common AWS vulnerabilities detection, guaranteeing no resource is missed. Without it, patch metrics could be skewed, and hidden systems become prime targets to be exploited.
4. Validate Patches and Conduct Routine Drills: Despite the best planning and execution, patch rollouts can fail or cause conflicts. Periodic validation scans ensure that updates work as intended, and resilience tests show how teams would handle it if a critical vulnerability is found. Drills also help to build up communication channels between the security, operations, and management teams. Over time, these exercises embed vigilance into daily processes, making AWS vulnerability remediation swift and reliable.

Why SentinelOne for AWS Vulnerability Assessment?

SentinelOne delivers powerful security specifically designed for AWS environments. You can get real-time protection across your entire AWS infrastructure. They will defend everything from EC2 instances to EKS containers, ECS, S3, FSxN, and NetApp filers.

When you use SentinelOne for AWS vulnerability assessment, you’ll have a unified platform that provides code-to-cloud security. The Offensive Security Engine simulates attacks safely on your cloud infrastructure to find truly exploitable vulnerabilities. You won’t waste time on false positives. SentinelOne is an AWS technology partner with over 7 AWS competencies and 20+ integrations. If you need enhanced visibility, you can use their integrations with Amazon Security Lake, AppFabric, Security Hub, and GuardDuty.

Deployment is simple and DevOps friendly, plus SentinelOne enforces shift-left security. It grants you full visibility into your AWS environment. You can find threats faster with its AI-powered solution. The platform automatically detects and blocks malicious processes in real-time. SentinelOne works across AWS regions worldwide. It provides instant visibility into your digital environment with rich context and correlation. If you have to remediate issues, SentinelOne offers automated fixes.

All SentinelOne solutions are available in the AWS Marketplace via Private Offer. You can start protecting your AWS environment right away without complex setup procedures. Before you face an attack, make sure you have the right tools in place.

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Conclusion

Effective AWS vulnerability assessment demands more than an occasional scan or piecemeal tool usage. Since AWS’s shared responsibility model requires customers to secure the operating system layers and configurations, a structured approach is crucial. By combining continuous scanning, real-time threat intelligence, and a robust AWS vulnerability assessment policy, organizations can minimize exploit windows, keep downtime at bay, and maintain trust with stakeholders. While cloud footprints continue to grow, practices such as least privilege, automated patch orchestration, and unified dashboards are mandatory for achieving consistent results. In such a dynamic environment, having a clear security strategy, proper security tools, and the organization’s personnel on the same page is crucial.

Looking ahead, it is critical to continue the use of AWS-native solutions, which can be supplemented by utilizing third-party platforms. SentinelOne Singularity™ Cloud Security builds upon these efforts by integrating autonomous detection, efficient patching, and comprehensive analytics – features that change the way you approach threats in the AWS cloud. From real-time scanning to orchestrated remediation, SentinelOne’s features are well-positioned for a future where the threat landscape continues to evolve. By incorporating such automation, organizations benefit from shorter time to resolution and improved insight into dynamic workloads.

Interested in strengthening your AWS vulnerability assessment best practices with an intelligent, integrated platform? Contact SentinelOne today to discover how our solution advances your AWS vulnerability remediation capabilities at every turn.