惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

博客园 - 司徒正美
Jina AI
Jina AI
Microsoft Azure Blog
Microsoft Azure Blog
博客园 - 三生石上(FineUI控件)
宝玉的分享
宝玉的分享
MyScale Blog
MyScale Blog
I
InfoQ
爱范儿
爱范儿
Microsoft Security Blog
Microsoft Security Blog
酷 壳 – CoolShell
酷 壳 – CoolShell
Stack Overflow Blog
Stack Overflow Blog
T
Tailwind CSS Blog
D
DataBreaches.Net
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
T
The Blog of Author Tim Ferriss
B
Blog
阮一峰的网络日志
阮一峰的网络日志
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
月光博客
月光博客
雷峰网
雷峰网
Recent Announcements
Recent Announcements
量子位
B
Blog RSS Feed

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
Secure your cloud environment from end to end with Datado...
Cliff Kim · 2024-12-02 · via Datadog | The Monitor blog
Cliff Kim

Cliff Kim

Infrastructure-as-code (IaC) tools like Terraform and CloudFormation allow teams to define, manage, and provision their cloud infrastructure using code, as opposed to clicking through consoles or executing commands via a CLI. IaC adoption is now widespread and helps teams increase productivity and efficiency, but it also introduces new surface area for mistakes, defects, and other risks. For example, IaC templates can include misconfigurations such as overprivileged access policies or hardcoded credentials, which could provide threat actors with a potential attack path.

To catch these issues, many organizations use one tool to scan IaC in pull requests and another to scan the deployed cloud environment. This approach can work temporarily for smaller environments—but as infrastructure grows, producing reports and managing detection rules across multiple tools becomes difficult.

Datadog IaC Security addresses these challenges by surfacing IaC misconfigurations so you can monitor and mitigate risks from code to cloud. In this post we will discuss how Datadog IaC Security enables your team to:

  • Detect cloud misconfigurations in code before they get to production

  • View code and cloud misconfigurations together in one place

  • Unify detection rules across code and infrastructure

Detect cloud misconfigurations in code before they get to production

IaC scanning is most commonly done in two places: in pull requests where new changes are suggested and in pipelines where IaC is processed and prepared for deployment. With Terraform, for example, scanning at the pull request stage involves parsing the Terraform HCL for misconfigurations in code. Scanning at the pipeline stage involves looking at the Terraform plan or state to see if there are misconfigurations in planned changes or existing infrastructure.

With Datadog IaC Security, you can install a GitHub app that will scan the Terraform HCL changes within pull requests. When misconfigurations are found, Datadog will leave a comment directly on the pull request with details about the finding and remediation steps where applicable. This keeps developers within the tool where code review normally happens and prevents context-switching, which is inefficient and error-prone. In the first half of 2025, we will introduce IaC scanning within pipelines via CLI.

Pull request with comments from Datadog IaC Security

View code and cloud misconfigurations together in one place

In addition to commenting on pull requests that contain misconfigured code, Datadog IaC Security also enables you to view all IaC issues in the Cloud Security Misconfigurations Explorer. Simply toggle the Explorer to Static view to see the list of IaC findings with severity and code location.

List of findings in Datadog IaC Security

Clicking into a misconfiguration finding will open the side panel where you can find additional details, including a brief description of the IaC rule associated with the finding, a preview of the offending code, and suggested steps for remediation.

Finding in Datadog IaC Security with detail side panel

Unify detection rules across code and infrastructure

In Datadog Cloud Security, out-of-the-box and custom cloud misconfiguration rules are written in the Rego policy language and executed using Open Policy Agent. Datadog IaC Security uses the same engine and rule language which makes writing and managing rules easier for your team as your cloud environment grows.

Datadog IaC Security offers will come with several out-of-the-box rules to help you catch common IaC misconfigurations, such as unencrypted EBS volumes and unsafe YAML deserializations. By detecting these issues at the pull request stage, IaC Security helps you prevent these types of misconfigurations from ever reaching your production environment.

Secure your IaC with Datadog

Datadog IaC Security provides end-to-end coverage of your cloud environment, helping you detect issues before they make it to production. IaC Security also integrates seamlessly into your developer workflows to provide a unified view of findings across code and cloud. Because you can use IaC Security alongside Cloud Security and other Datadog products, you can manage all of your detection rules in a single platform.

To learn more, check out our IaC Security documentation. If you’re not already using Datadog, get started today with a 14-day free trial.