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Datadog | The Monitor blog

Introducing our open source AI-native SAST Instrument and monitor Boomi integration flows with OpenTelemetry and Datadog Not all index scans are equal: How we cut query latency by over 99% Platform engineering metrics: What to measure and what to ignore Integrate Recorded Future threat intelligence with Datadog Cloud SIEM CI/CD security: threat modeling using a MITRE-style threat matrix CI/CD security: How to secure your GitHub ecosystem Ingress NGINX is EOL: A practical guide for migrating to Kubernetes Gateway API Operating agentic AI with Amazon Bedrock AgentCore and Datadog LLM Observability: Lessons from NTT DATA Introducing the Datadog Code Security MCP Capture and analyze custom heatmaps in Session Replay Understand session replays faster with AI summaries and smart chapters Monitor ClickHouse query performance with Datadog Database Monitoring How we designed empathetic alert sounds for on-call engineers Search and act across Datadog to resolve issues faster with Bits Assistant Measure the business impact of every product change with Datadog Experiments Analyzing round trip query latency Configuring JavaScript caches for better performance Introducing Bits AI Dev Agent for Code Security Datadog achieves ISO 42001 certification for responsible AI Monitor Nutanix clusters, hosts, and VMs with Datadog Monitor Juniper Mist in Datadog A new Host Map for modern infrastructure Annotate traces to improve LLM quality with Datadog LLM Observability What’s new in Cloud SIEM: AI-powered investigations, enhanced threat intelligence, and scalable security operations Explore Kubernetes with native OpenTelemetry data Monitor Oracle Fusion Cloud Applications with Datadog Announcing the Datadog Terraform provider v4.0.0 Scaling Kubernetes workloads on custom metrics How to design cloud environments for AI-powered threat analysis Monitor Aruba Central in Datadog How we centralize and remediate risks with Datadog Case Management Accelerate incident response with Datadog and ServiceNow Monitor your application and network load balancer logs Understanding Karpenter architecture for Kubernetes autoscaling Tools for collecting metrics and logs from Karpenter Monitor Karpenter with Datadog What your product data is actually saying Key metrics for monitoring Karpenter Securing Datadog’s platform in the AI age: The role of observability data Four ways engineering teams use the Datadog MCP Server to power AI agents Approaching your observability migration with the right mindset Meet the new Bits AI SRE: Deeper reasoning, twice as fast Key learnings from the 2026 State of DevSecOps study Use plain English to query your multi-cloud infrastructure in Resource Catalog Simplifying troubleshooting across the user journey with Datadog Synthetic Monitoring Protect your OCI resources with Datadog Cloud Security This Month in Datadog - 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Detect malware in your containers with Datadog Workload Protection
Parag Baxi, Nathaniel Beckstead, Aaron Kaplan · 2024-03-19 · via Datadog | The Monitor blog

Detecting malware in container environments can be a major challenge due to the rapid development of malicious code, the proliferation of insecure container images, and the multilayered complexity of container stacks. Staying ahead of attackers means tracking the constant evolution of malware and rooting out threats in your codebase at the expense of considerable compute.

Datadog Workload Protection provides a unified platform for malware detection across your containerized environment. Workload Protection builds on Datadog’s internal threat intelligence by ingesting from third-party feeds—beginning with MalwareBazaar, with more to come—in order to detect malicious software running in your containers, so you can immediately identify and remove threats.

In this post, we’ll show you how Workload Protection enables you to:

  • Detect malware with enhanced precision using crowd-sourced threat intelligence

  • Identify and assess the impact of malicious code running on your systems

Detect malware with enhanced precision using crowd-sourced threat intelligence

Datadog maintains an internal threat intelligence feed that generates security signals for our customers based on indicators of compromise (IOCs) identified by our security researchers. Augmenting our internal threat intelligence with data from third-party feeds such as MalwareBazaar helps us proactively monitor the cutting edge of malicious code. MalwareBazaar’s crowd-sourced database of malware samples promotes communal threat intelligence, and its users submit hundreds of unique malware samples every day.

But crowd-sourcing can also increase the potential for false-positive identifications of malware. Datadog Workload Protection filters the MalwareBazaar feed—for example, by excluding anonymous uploads in order to eliminate submissions from potentially untrustworthy sources—and uses fuzzy hashing in order to minimize the potential for false positives while casting a wide net.

This type of malware detection can be resource-intensive, since it involves hashing and comparing large volumes of data. To prevent strain on your resources, Workload Protection malware detection is executed on the backend, in our servers.

Next, we’ll provide a more hands-on look at what happens when Workload Protection detects malware, and how it sets you up to respond.

Identify and assess the impact of malicious code running on your systems

When Workload Protection identifies malware in your code base, it generates a security signal. You can view and search your security signals in the Workload Protection Signals Explorer.

An overview of security signals in the Workload Protection Signals Explorer

Malware-triggered security signals are automatically assigned a severity level of critical. As shown above, malware-based security signals are clearly labeled in the Signals Explorer, but you can also configure notifications to point you directly to high-severity or critical security signals such as this.

The Signals Explorer provides basic details on each security signal, such as a brief summary of what occurred and details on precisely when and where the signal was generated. You can select one of these signals from the explorer to quickly get more context and zero in on the malicious code.

Inspecting a security signal triggered by Workload Protection malware detection.

The security signal overview shown above, at right, lets you determine exactly where the malware was found. It specifies the affected container and host and provides a process tree to show you the precise context of the detected malware. It also provides a link to the specific entry in the MalwareBazaar database for the detected malware, so you can assess the nature of the threat.

A MalwareBazaar database entry.

With all of this information, you can quickly take action to contain the issue as necessary and resume your investigation by pivoting to other resources in Datadog. For example, you might want to pause or isolate the affected container, then navigate to the Context tab of the security signal to survey key metrics from the affected host from around the time of the signal, which may be important for determining the impact of the malware.

The context tab for a security signal in Workload Protection.

Or, you could navigate to the Related Signals tab to inspect any related suspicious activity flagged by your detection rules.

For a security-focused overview of data from your host, you can select “Investigate Host” to quickly pivot to the out-of-the-box Host Investigation dashboard. Here you can find a breakdown of security signals, infrastructure metrics, and other data that could guide your investigation of malware detected in your host.

The out-of-the-box Host Investigation dashboard.

For example, you might want to examine the Network Activity section of the Host Investigation dashboard to look for signs of suspicious activity, such as outgoing connections to unusual IP addresses or domains, or spikes in traffic.

The Network Activity section of the Host Investigation dashboard.

You may also want to pivot to Datadog Log Management to analyze logs for the affected container in order to determine the scope of the malicious activity.

Keep your containers secure with Datadog Workload Protection

Datadog Workload Protection offers a unified platform for malware detection that leverages our internal threat intelligence as well as real-time data from MalwareBazaar so you can keep your containers secure and quickly hone in on malicious code. Filtering MalwareBazaar’s crowd-sourced data helps us proactively monitor the cutting edge of malicious code while minimizing the potential for false positives. And because our malware detection is performed on our own servers, rather than your hosts, Workload Protection spares you the high computational overhead of hashing and comparing large volumes of data.

You can check out our Workload Protection docs to learn more. And, if you’re new to Datadog, you can sign up for a 14-day free trial.