Datadog

Software Composition Analysis (SCA)

Datadog

Datadog Software Composition Analysis (SCA) is a comprehensive solution designed to identify, prioritize, and remediate security vulnerabilities and licensing risks within open-source libraries used across the software development lifecycle, from code repositories to production environments. It leverages both static analysis, scanning code in CI/CD pipelines and IDEs, and runtime analysis, observing libraries in active services, to provide end-to-end visibility. The platform helps DevOps and security teams mitigate risks by offering a unified view of vulnerabilities, enriched with real-time observability context and a proprietary severity score. This enables organizations to proactively address issues, ensure compliance with licensing standards, and streamline incident response by providing actionable remediation guidance and seamless integration with existing development workflows. Datadog SCA aims to reduce the attack surface introduced by third-party dependencies and enhance the overall security posture of applications.

Workload Protection

Datadog

Datadog Workload Protection is a comprehensive cloud workload protection platform (CWPP) designed to safeguard production workloads across diverse environments, including Linux and Windows hosts, Docker containers, and Kubernetes clusters. It leverages deep, in-kernel analysis to monitor file, network, and process activity in real-time, identifying and mitigating threats. The platform provides out-of-the-box and customizable security rules, enhanced by internal and third-party threat intelligence for advanced malware detection. Key capabilities include real-time threat detection, file integrity monitoring, process execution monitoring, DNS activity monitoring, and kernel-level attack detection. Beyond active threat prevention, it offers runtime posture monitoring to identify and remediate risky behaviors, and advanced incident investigation tools like Execution Contexts, an Investigation Graph, and a Threat Timeline to help security teams correlate events and understand attack narratives. Datadog Workload Protection integrates seamlessly into the broader Datadog platform, utilizing the existing Datadog Agent for efficient deployment and unified visibility, making it ideal for organizations with complex, cloud-native architectures and DevOps/Security teams seeking deep operational and security insights.

Runtime Code Analysis (IAST)

Datadog

Datadog Runtime Code Analysis (IAST) is a cloud-based Interactive Application Security Testing solution designed to continuously monitor applications in production environments for real code-level vulnerabilities. Leveraging the same tracing libraries as Datadog APM, it observes legitimate application traffic and analyzes data flow from sources to sinks in real-time. This approach accurately identifies vulnerabilities such as SQL Injection, Command Injection, Path Traversal, and LDAP Injection, achieving 100% on the OWASP Benchmark with minimal false positives. The product provides actionable insights, including code snippets, affected file and method names, and line numbers, to accelerate remediation. It seamlessly integrates into existing DevOps and security workflows, fostering collaboration and improving overall application security posture through continuous feedback and guided remediation steps. Datadog IAST is a core component of the broader Datadog Code Security suite, offering end-to-end visibility from development to production.

Sensitive Data Scanner

Datadog

Datadog's Sensitive Data Scanner is a comprehensive, real-time solution designed to identify, classify, and protect sensitive information across an organization's entire technology stack. It actively scans diverse data sources, including application logs, performance traces (APM), real user monitoring (RUM) events, LLM Observability traces, code repositories, and cloud environments (e.g., AWS S3, RDS instances), to detect personally identifiable information (PII), payment card industry (PCI) data, API keys, and other confidential data. The scanner leverages a rich library of predefined rules and supports custom regex patterns for precise identification. Upon detection, it can automatically redact, hash, or mask sensitive data, preventing accidental exposure and mitigating the risk of data breaches. This capability is crucial for maintaining compliance with stringent data protection regulations such as GDPR, HIPAA, and CCPA. By providing continuous visibility into sensitive data flows and integrating with Datadog's broader security and observability platform, the Sensitive Data Scanner enables organizations to proactively manage data security posture, streamline compliance efforts, and accelerate incident response for sensitive data-related issues. It supports both in-cloud and on-premises scanning via Observability Pipelines, offering flexible deployment options to secure data before it leaves the customer's environment or during ingestion into the Datadog platform.

Vulnerability Management

Datadog

Datadog Vulnerability Management, a core component of Datadog's Cloud Security Management platform, provides comprehensive capabilities for identifying, prioritizing, and remediating security vulnerabilities across cloud-native environments. It continuously scans a wide array of resources, including container images, hosts, host images, and serverless functions, throughout the entire software development lifecycle—from CI/CD pipelines to live production. By leveraging real-time observability and a proprietary Datadog Severity Score, the platform intelligently prioritizes exploitable vulnerabilities based on factors like CVSS score, sensitive data exposure, environment criticality, and exploit availability. This allows security and DevOps teams to focus on the most critical threats, streamline remediation workflows through automation and integrations with tools like Jira, and maintain compliance with various regulatory standards such as SOC2, PCI, HIPAA, and FedRamp. Datadog Vulnerability Management aims to reduce the attack surface, improve security posture, and foster collaboration between security and development teams by providing a unified view of security risks and actionable insights.

Cloud Security Posture Management (CSPM)

Datadog

Datadog Cloud Security Posture Management (CSPM) is a comprehensive SaaS-based solution designed to continuously monitor and assess the security posture of an organization's cloud environments. It provides real-time visibility into misconfigurations, vulnerabilities, and compliance risks across various cloud providers (AWS, Azure, GCP) and containerized environments, including Kubernetes. The platform helps security, DevOps, and compliance teams identify and remediate security issues faster by offering continuous scanning, detailed alerts, and actionable insights. Datadog CSPM integrates seamlessly with the broader Datadog observability platform, allowing users to correlate security findings with infrastructure metrics, logs, and application performance data for a unified view of their cloud security. Its core purpose is to prevent data breaches, account hijacking, and ensure adherence to industry standards and regulatory requirements, ultimately strengthening the overall cloud security posture.

IaC Security

Datadog

Datadog IaC Security is a cloud-native solution designed to proactively identify and mitigate security risks within Infrastructure as Code (IaC) templates, such as Terraform and Kubernetes configurations, before they are deployed to production environments. By integrating directly into developer workflows and source code repositories like GitHub, GitLab, and Azure DevOps, it enables organizations to "shift security left," detecting misconfigurations, policy violations, and insecure defaults early in the development lifecycle. The platform continuously scans IaC files, analyzes commits, and provides actionable insights, including detailed explanations of risks, their potential impact, and suggested remediation steps with code snippets. It facilitates collaboration between security and development teams through features like automated pull request comments, configurable PR Gates to block risky changes, and integration with project management tools like Jira. Datadog IaC Security also offers comprehensive dashboards for tracking security posture over time, allowing teams to monitor trends, prioritize remediation efforts, and ensure compliance with security standards. Leveraging the same policy engine as Datadog Cloud Security, it provides a unified approach to managing security rules across code and deployed cloud infrastructure, preventing common issues like overly permissive access controls, unencrypted resources, and exposed services.

App and API Protection (AAP)

Datadog

Datadog App and API Protection (AAP) is a Software-as-a-Service (SaaS) solution that delivers unified security and observability for web applications and APIs. It integrates seamlessly with Datadog's existing observability platform, leveraging Application Performance Monitoring (APM) data and tracing libraries to provide real-time threat detection, investigation, and prevention. AAP extends beyond traditional perimeter defenses by offering in-app protection, including an In-App Web Application Firewall (WAF) and Exploit Prevention (Runtime Application Self-Protection - RASP technology), to defend against a broad spectrum of attacks such as SQL injection, Cross-Site Scripting (XSS), Server-Side Request Forgery (SSRF), and account takeover attempts. The platform automatically discovers all APIs, including undocumented ones, assesses their security posture against industry best practices like the OWASP API Top 10, and facilitates the identification and remediation of vulnerabilities. Designed for both Security and DevOps teams, AAP secures modern, distributed, and serverless application environments, providing continuous protection and actionable insights into attack patterns and threat actors. It also offers specialized protection for AI applications against emerging threats like prompt injection.

Cloud Infrastructure Entitlement Management (CIEM)

Datadog

Datadog Cloud Security Identity Risks, formerly known as Cloud Infrastructure Entitlement Management (CIEM), is a Software-as-a-Service (SaaS) solution designed to proactively identify, monitor, and remediate identity and access risks across dynamic multi-cloud environments. It addresses the critical challenge of managing complex permissions for both human and machine identities within cloud infrastructure, which often leads to misconfigurations, excessive privileges, and potential attack vectors. The platform continuously scans cloud environments, including AWS, Azure, and Google Cloud, to detect and prioritize issues such as lingering administrative privileges, privilege escalations, permission gaps (unused or overly broad access), large blast radii, and cross-account access. By providing deep visibility into who has access to what, how they obtained it, and how it's being used, Datadog Cloud Security Identity Risks helps organizations effectively enforce the principle of least privilege. It offers actionable insights, suggested policy remediations, and automated workflows to quickly mitigate identified risks, thereby securing cloud infrastructure from IAM-based attacks and enhancing overall security posture and compliance with industry standards.

Secret Scanning

Datadog

Datadog Secret Scanning is a crucial component of the Datadog Code Security platform, designed to proactively identify, validate, and prevent the exposure of sensitive credentials within an organization's codebase, repositories, and CI/CD pipelines. It scans source code, configuration files, and other artifacts for hardcoded secrets such as API keys, tokens, and passwords. A key capability is its real-time validation of detected secrets with third-party providers, which helps security teams prioritize remediation by distinguishing between active, exploitable credentials and those that are merely syntactically correct but inactive. This "shift-left" security approach integrates directly into developer workflows, enabling automatic blocking of commits or merges that contain sensitive information, thereby preventing secrets from reaching production environments. The solution also extends its protection to AI-generated code, ensuring that machine-generated snippets do not inadvertently leak confidential credentials. By providing context-enriched findings and a severity score, Datadog Secret Scanning helps organizations reduce false positives, accelerate secure code delivery, and maintain a clean, compliant codebase, ultimately mitigating the risk of unauthorized access and data breaches.

Static Code Analysis (SAST)

Datadog

Datadog's Static Code Analysis (SAST) is a core component of its comprehensive Code Security platform, designed to identify security vulnerabilities and code quality issues within an application's source code, bytecode, or binaries *before* the code is executed. This "clear-box" testing methodology integrates seamlessly into the Software Development Life Cycle (SDLC), specifically within Integrated Development Environments (IDEs), pull request workflows, and Continuous Integration/Continuous Delivery (CI/CD) pipelines. Its primary purpose is to enable developers and security teams to detect and remediate security flaws and adherence to coding standards as early as possible, thereby preventing vulnerable code from reaching production environments. The solution supports various programming languages and offers features like inline feedback, automated suggested fixes (including AI-powered suggestions), and diff-aware scanning to accelerate the review process. By centralizing vulnerability management and providing actionable insights, Datadog SAST helps organizations improve their overall security posture, reduce technical debt, and maintain developer velocity by shifting security left in the development process. It is part of Datadog's larger observability and security platform, leveraging existing integrations for a unified view of application health and security.

Cloud SIEM

Datadog

Datadog Cloud SIEM is a cloud-native Security Information and Event Management (SIEM) platform designed to provide comprehensive threat detection, investigation, and response capabilities across dynamic cloud and hybrid environments. It unifies operational and security logs from over 1,000 sources, including cloud services, on-premises systems, networks, identity providers, endpoints, and SaaS applications, into a single platform. Leveraging machine learning and a vast library of over 800 out-of-the-box detection rules aligned with the MITRE ATT&CK framework, it continuously scans live log streams to identify threats in real-time. The platform enriches security signals with risk-based insights, including Cloud Security Management data, to prioritize critical incidents. It facilitates accelerated incident response through integrated Security Orchestration, Automation, and Response (SOAR) workflows, collaborative case management, and AI-driven investigation capabilities. Datadog Cloud SIEM aims to break down silos between security, development, and operations teams by providing a unified view of observability and security data, enabling faster and more efficient threat mitigation and improved security posture. It offers flexible log retention for historical analysis and forensic review, supporting compliance and long-term security insights.