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

罗磊的独立博客
小众软件
小众软件
The Cloudflare Blog
博客园 - 【当耐特】
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
酷 壳 – CoolShell
酷 壳 – CoolShell
WordPress大学
WordPress大学
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
V
Visual Studio Blog
量子位
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
美团技术团队
S
SegmentFault 最新的问题
宝玉的分享
宝玉的分享
博客园 - 叶小钗
月光博客
月光博客
Apple Machine Learning Research
Apple Machine Learning Research
T
Tailwind CSS Blog
博客园 - 聂微东
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
J
Java Code Geeks
Y
Y Combinator Blog
D
Docker
Microsoft Azure Blog
Microsoft Azure Blog

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 Auth0 with Datadog
2020-09-30 · via Datadog | The Monitor blog

Auth0 provides identity as a service (IDaaS), allowing you to secure your apps and APIs without having to write your own authorization code. Auth0 can work with social identity providers (IdP) like Google and Facebook so your users can access your app by using their existing accounts for authentication. You can also use an existing enterprise identity provider (e.g., LDAP) to allow your users to leverage single sign-on (SSO) across multiple apps. Auth0 helps you implement login features like these—along with options like multi-factor authentication (MFA) and passwordless authentication—while removing the burden of maintaining your own authentication functionality.

Datadog’s Auth0 integration allows you to monitor and analyze Auth0 logs to detect user actions that could indicate security concerns and to better understand how users interact with your application. You can graph and alert on the number of logins to your application and use data from your Auth0 logs to automatically trigger notifications based on threat detection rules you define. And you can easily configure long-term retention to meet regulatory requirements by archiving Auth0 logs in your preferred cloud storage service.

Analyze and audit Auth0 activity

The Log Explorer shows Auth0 logs and facet controls. The selected Event Name values indicate failed logins.

As Datadog ingests your Auth0 logs, it sends them through a log processing pipeline. The pipeline automatically parses each log to extract key data as standard attributes, which provide a naming convention you can use to easily correlate events from multiple sources. Datadog automatically maps the Auth0 event type code to evt.name, which appears as the standard Event Name facet. You can use this facet to analyze user activity such as account creation and deletion, password changes, and more. In the screenshot above, we’ve filtered the view to graph log data only from apps that use Auth0 as an authentication provider (source:auth0), and to display logs that have one of the event names that indicate a failed login.

Visualize key Auth0 events

You can use log analytics to visualize log data in Datadog, revealing potentially suspicious patterns in user activity. For example, logins and multi-factor authentications commonly fail due to user error, but if your log data shows a rising frequency of events like these, it could be evidence of automated attacks against your application. In the screenshot below, the graph visualizes successful logins in orange and failed MFA logins in red. To investigate a spike like the one shown here, you can click a point on the graph to see related logs that give you deeper context on the issue.

An area graph shows the rate of failed OTP authentications rising relative to the rate of successful logins.

Auth0’s anomaly detection feature automatically blocks an IP address that has generated an abnormally high rate of unsuccessful login attempts. A rising rate of blocking events could indicate an attack. The screenshot below shows how you can graph events like blocked IP addresses as well as attempted logins using breached passwords.

A graph shows the rate at which Auth0 is blocking suspect IP addresses and detecting the use of breached passwords.

You can use a table like the one shown below—which lists the number of requests sent from the IP addresses blocked by Auth0—to investigate further.

A table titled Blocked IPs sending most login requests has columns for IP address, city, country, and count.

In the next section, we’ll show you how you can also use Datadog Cloud SIEM to automatically notify you of potential issues detected in your Auth0 data.

Use Cloud SIEM and threat notifications

Datadog Cloud SIEM uses threat detection rules to alert you when a threat is detected. A collection of out-of-the-box rules for Auth0 logs makes it easy to monitor for some common threats in real time—such as a user authenticating from multiple countries, which indicates an attempt to compromise a user’s credentials.

You can also create custom rules based on thresholds you define for identifying suspicious behavior. Datadog analyzes Auth0 logs in real time to detect any violations of your threat detection rules. If a rule is violated, Datadog will alert your team via email, Slack, Jira, or other collaboration tools that suit your incident response process.

In the screenshot below, we’ve configured Datadog to alert the security operations team via email if there are five failed logins and a successful login from a single user within five minutes, which could indicate a possible brute force attack.

The security rules page defines a log detection rule's queries (which describe what to monitor) and cases (which describe when to trigger).

Your security operations team can use the information in an alert like this to investigate and remediate the threat. If the information in the alert points to a specific IP address that shows a pattern of suspicious activity, you can investigate further by correlating your Auth0 logs with your other application logs. If necessary, you can take additional measures such as blocking the IP address in your web application firewall.

Extend your security visibility with Datadog

Datadog’s Auth0 integration brings deep visibility into your Auth0 logs, which—alongside Datadog Cloud SIEM and integrations for more than 1,000 other technologies—means you can ensure the security of your applications and the infrastructure that runs them.

To enable Auth0 monitoring in Datadog, check out our documentation. If you’re not already using Datadog, sign up today for a free 14-day trial.