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

aimingoo的专栏
aimingoo的专栏
S
Securelist
博客园 - Franky
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
IT之家
IT之家
GbyAI
GbyAI
Microsoft Azure Blog
Microsoft Azure Blog
The Cloudflare Blog
云风的 BLOG
云风的 BLOG
N
News and Events Feed by Topic
AI
AI
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
Schneier on Security
Schneier on Security
Attack and Defense Labs
Attack and Defense Labs
Vercel News
Vercel News
腾讯CDC
Google DeepMind News
Google DeepMind News
K
KPMG report finds enterprise disconnect between AI and its ROI | CIO
M
MIT News - Artificial intelligence
WordPress大学
WordPress大学
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
N
Netflix TechBlog - Medium
量子位
S
Schneier on Security
Hacker News: Ask HN
Hacker News: Ask HN
Cyberwarzone
Cyberwarzone
S
Security Affairs
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
N
News and Events Feed by Topic
T
Tenable Blog
PCI Perspectives
PCI Perspectives
MyScale Blog
MyScale Blog
L
Lohrmann on Cybersecurity
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
C
Cyber Attacks, Cyber Crime and Cyber Security
W
WeLiveSecurity
N
News | PayPal Newsroom
P
Proofpoint News Feed
O
OpenAI News
C
CERT Recently Published Vulnerability Notes
B
Blog
Cisco Talos Blog
Cisco Talos Blog
Microsoft Security Blog
Microsoft Security Blog
V
Visual Studio Blog
MongoDB | Blog
MongoDB | Blog
大猫的无限游戏
大猫的无限游戏
A
Arctic Wolf
Y
Y Combinator Blog
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
Spread Privacy
Spread Privacy

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 - February 2026 Amazon EC2 security: How misconfigured and public AMIs expand your cloud attack surface Enable end-to-end visibility into your Java apps with a single command Measure and improve mobile app startup performance with Datadog RUM Evaluating our AI Guard application to improve quality and control cost Identify untested code across every level of your codebase Make use of guardrail metrics and stop babysitting your releases Monitor Versa Networks SD-WAN performance in Datadog Improve performance and reliability with APM Recommendations Remediate transitive vulnerabilities faster with Datadog Software Composition Analysis Generate audit-ready vulnerability and compliance reports with Datadog Sheets Monitor Fortinet FortiManager performance in Datadog Improve test coverage across codebases with Datadog Code Coverage Move fast, don’t break things: Consistent testing standards at scale Enrich logs with ServiceNow CMDB context before routing to any SIEM or logging tool Monitor Lustre with Datadog Make faster, better product decisions with Datadog Product Analytics Surface and remediate runtime posture issues with Workload Protection Findings Protect agentic AI applications with Datadog AI Guard How to optimize JavaScript code with CSS Trace Google Pub/Sub workloads in Cloud Run with Datadog Detect human names in logs with ML in Sensitive Data Scanner How we cut our NLQ agent debugging time from hours to minutes with LLM Observability Debug PostgreSQL query latency faster with EXPLAIN ANALYZE in Datadog Database Monitoring Datadog acquires Propolis Unify and correlate frontend and backend data with retention filters Scale compliance across global frameworks with Datadog Cloud Security Monitor Arista VeloCloud SD-WAN performance with Datadog Building reliable dashboard agents with Datadog LLM Observability Simplify log collection and aggregation for MSSPs with Datadog Observability Pipelines Mitigation for Node.js denial-of-service vulnerability affecting Datadog APM Automate flaky test fixes with the Bits AI Dev Agent and Test Optimization How we built an AI SRE agent that investigates like a team of engineers Datadog integrations 2025 recap: Observability for AI, security, and hybrid cloud Design effective executive dashboards with Datadog Implement dbt data quality checks with dbt-expectations Bring faster visibility into AWS Lambda functions with remote instrumentation Troubleshoot faster with the GitLab Source Code integration in Datadog How Cambia Health Solutions saved $30,000 monthly with Cloud Cost Management and the Datadog Resource Catalog Normalize any logs for Cloud SIEM with Datadog's OCSF processor Optimizing Datadog at scale: Cost-efficient observability at Zendesk Detect, diagnose, and resolve network issues easily with CNM Network Health Connect engineering errors to user impact in early-stage products Cilium configuration for Kubernetes operations at scale Designing feedback loops for progressive delivery Ship features faster and safer with Datadog Feature Flags Choosing the right OpenTelemetry Collector distribution Route your monitor alerts with Datadog monitor notification rules Automate Cloud SIEM investigations with Bits AI Security Analyst Cloud threat detection: How to identify risky activity across control and data planes Collecting Kafka performance metrics Monitoring Kafka with Datadog Monitoring Kafka performance metrics
Visualize cloud security relationships with Datadog Security Graph
2025-06-10 · via Datadog | The Monitor blog
Jean-Claude Kuo

Jean-Claude Kuo

For developers and security engineers alike, one of the most persistent challenges in cloud security is making sense of how compute, storage, identity, and networking components interact. Traditional security tools often lack the ability to surface multi-hop access paths, making it difficult to answer questions like: “Which EC2 instances can access sensitive S3 buckets, and are any of them exposed to the internet?” Datadog Security Graph addresses this problem by modeling your cloud environment as a dynamic, relationship-aware graph. Built on data from Datadog Cloud Security, it enables you to visualize and query the real-world connections between cloud resources, helping you surface indirect access paths, assess identity risk, and respond more effectively to emerging threats.

In this post, we’ll show you how to use Datadog Security Graph to:

Identify potential attack paths within your cloud resources

Security Graph reimagines your cloud environment as a graph of nodes and relationships. Resources such as EC2 instances, IAM roles, S3 buckets, and security groups are represented as nodes, while access relationships, trust relationships, and network exposure are modeled as edges. This approach has several advantages:

  • It captures both direct and transitive relationships, such as a role assuming another role that has access to a resource.
  • It enables you to spot indirect access paths and risk exposure that would otherwise remain hidden in IAM policies or configuration files.
  • It reflects how attackers think, identifying possible pivot points between resources.
  • It gives security teams a complete, contextual view of risk across their cloud environments.

While piecing together relationships across your cloud resources manually would be time-consuming and error-prone with traditional inventory tools, Security Graph combines data from Agentless and Agent-based cloud scanning to offer a detailed view of these relationships. It includes several features that help teams investigate and respond to risk:

  • Prebuilt queries for common security questions, such as, “Which publicly accessible EC2 instances have administrative IAM roles?”
  • A no-code query builder to help you dive deeper and find potentially risky relationships among your cloud resources
  • Interactive visualizations that let you explore cloud resource graphs and view metadata, tags, and linked security findings
  • A tabular view for analyzing and exporting results at scale

For example, let’s say you’re trying to find any publicly accessible EC2 instances that can access S3 buckets containing sensitive data. This type of investigation requires analyzing a multi-hop path that might look like this:

  1. A public EC2 instance is associated with an instance profile.
  2. That instance profile is bound to IAM Role A.
  3. IAM Role A has a policy that allows it to assume IAM Role B using sts:AssumeRole.
  4. IAM Role B has a permission policy that grants access to specific S3 buckets (e.g., s3:GetObject, s3:ListBucket).

Security Graph makes this entire access chain visible and queryable, enabling you to visualize the exact kinds of resources and paths you’re looking for.

See relationships across your cloud resources in Datadog Security Graph

This visualization reveals not just whether access exists, but how it’s granted, enabling teams to assess whether those paths are expected, misconfigured, or overly permissive. With this information in hand, you can remediate any resources where these configurations are unwanted or excessive, limiting your infrastructure’s risk exposure.

Analyze identity policies with Access Insights

Security Graph also powers Access Insights, which calculates effective permissions for any identity or resource by analyzing:

  • Direct policies (inline, AWS-managed, customer-managed)
  • Indirect policies (assumed roles, group memberships)
  • Resource-based permissions (service control policies, permission boundaries)

When you select a resource in the Security Graph, you’ll bring up a detailed side panel that includes these insights. This data helps you answer questions such as:

  • What can this EC2 instance access?
  • Which roles or users can read from this S3 bucket?
Access Insights in Datadog Security Graph

By surfacing both explicit and transitive access paths, Access Insights helps you right-size IAM policies and reduce the potential for lateral movement.

Understand cloud risks holistically with Security Graph

Datadog Security Graph provides security and DevOps teams a real-time, relationship-based view of risks across their infrastructure, so they can:

  • Accelerate investigations: Visually trace access paths in seconds instead of reviewing IAM policies line-by-line.
  • Analyze blast radius: Understand the downstream effects of a compromised identity or misconfigured policy.
  • Perform proactive security reviews: Identify and remediate risky access paths before they reach production.

By modeling access the way attackers do—through connected paths rather than isolated nodes—Security Graph helps everyone make more informed decisions about infrastructure risk.

Datadog Security Graph is currently in preview and available to customers who use Datadog Cloud Security. Sign up for the preview and check out our documentation to get started. If you’re not yet using Datadog, you can sign up for a 14-day free trial.