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Sysdig Blog

Masterclass: AI is more than ChatGPT and LLMs CVE-2026-39987 update: How attackers weaponized marimo to deploy a blockchain botnet via HuggingFace Kubernetes 1.36 - New security features 5 steps to securing AI workloads Marimo OSS Python Notebook RCE: From Disclosure to Exploitation in Under 10 Hours Security briefing: March 2026 The Sysdig MCP server is now available in AWS Marketplace Risk isn’t reduced until you take action: How teams resolve issues in the cloud AI infrastructure security: Why it deserves its own category Three pillars for building effective runtime-powered cloud defense, the right way Closing the cloud security gap with runtime security Seeing risk isn’t stopping it: Why visibility alone isn’t enough TeamPCP expands: Supply chain compromise spreads from Trivy to Checkmarx GitHub Actions AI coding agents are running on your machines — Do you know what they're doing? Runtime security for AI coding agents: Protecting AI-assisted development How runtime insights power every cloud security use case CVE-2026-33017: How attackers compromised Langflow AI pipelines in 20 hours Inline Cloud Response: Accelerating AWS threat containment for SOC teams Runtime malware detection for AWS Fargate Detecting CVE-2026-3288 & CVE-2026-24512: Ingress-nginx configuration injection vulnerabilities for Kubernetes Malware detection with Sysdig Security briefing: February 2026 Leveling up Kubernetes Posture: From baselines to risk-aware admission Eliminating runtime blind spots: How CleanStart and Sysdig build continuous trust across the container lifecycle LLMjacking: From Emerging Threat to Black Market Reality Real risks live at runtime: Why CISOs must care about deep telemetry in 2026 Sysdig named a Leader in the Forrester Wave™: Cloud Native Application Protection Solutions, Q1 2026 How to run rootless containers AI-assisted cloud intrusion achieves admin access in 8 minutes Security briefing: January 2026 Securing GPU-accelerated AI workloads in Oracle Kubernetes Engine Bringing OSS runtime security to AWS: Falco integration with AWS Security Hub CSPM Our customers have spoken: Sysdig rated a Strong Performer in Gartner® Voice of the Customer for Cloud-Native Application Protection Platforms Protecting sensitive business data in preparation for the organization's Gen AI VoidLink threat analysis: Sysdig discovers C2-compiled kernel rootkits AI is still a workload: A practical guide to securing AI workloads How threat actors are using self-hosted GitHub Actions runners as backdoors How Sysdig Sage delivers AI-powered, real-world vulnerability management Security briefing: December 2025 Top 10 ways to get breached in 2026 EtherRAT dissected: How a React2Shell implant delivers 5 payloads through blockchain C2 Introducing runtime file integrity monitoring and response with Sysdig FIM How to detect multi-stage attacks with runtime behavioral analytics EtherRAT: DPRK uses novel Ethereum implant in React2Shell attacks Detecting React2Shell: The maximum-severity RCE vulnerability affecting React Server Components and Next.js The rise of AI agents: How autonomous AI Is transforming cloud security Kubernetes 1.35 - New security features The Urgency of Securing AI Workloads for CISOs Security briefing: November 2025 Quantum and the cloud: Science fiction turned security strategy Cloud security, the right way: What the industry should demand (and why "good enough" isn't) Return of the Shai-Hulud worm affects over 25,000 GitHub repositories Detecting CVE-2024-1086: The decade-old Linux kernel vulnerability that’s being actively exploited in ransomware campaigns What’s old is new again: How to demystify AI security with AIBOMs Securing Kubernetes with agentic cloud security How agentic cloud security reduces real risks Hunting reverse shells: How the Sysdig Threat Research Team builds smarter detection rules Shifting left with AI and MCP: Sysdig + Amazon Q Developer How Falco and Stratoshark close the gap between open source runtime detection and deep forensic analysis Investigating security issues with ChatGPT and the GitHub MCP server New runc vulnerabilities allow container escape: CVE-2025-31133, CVE-2025-52565, CVE-2025-52881 Harden your LLM security with OWASP Security briefing: October 2025 How agentic AI is changing cloud security Kubernetes Incident Response: Detect, investigate, and contain in under 10 minutes Sysdig recognized as a Cloud Security Leader in Latio Tech Cloud Security Market Report AI echolocation of cloud risks using Sysdig & Snyk MCP servers Sysdig MCP Server: Bridging AI and cloud security insights Understanding CVE-2025-49844: “RediShell” Critical Remote Code Execution in Redis How Sysdig secures your containers and Kubernetes Sysdig Security Briefing: September 2025 Cloud security, the right way: The 3 pillars of real-time defense Open source spotlight: Bringing web application security to Falco with Falcoya's Nginx plugin Malicious NPM packages: Are you exposed? 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Connecting runtime to source: Sysdig and Semgrep integration
2025-07-29 · via Sysdig Blog

In today’s complex cloud environments and mounting pressure, the last thing security teams need is a dead end. Yet, that’s often what a critical runtime finding becomes. We’ve all been there: you see a vulnerability actively running in production, but the trail goes cold. Where did it come from? Which team owns it? How do we implement the fix?

At Sysdig, we know that identifying an active vulnerability is only half the battle. That’s why our partnership with Semgrep is so important. We’re not just connecting two tools; we’re connecting the two most critical points in the security lifecycle: the moment a vulnerability is detected at runtime and the exact line of code where it was born.

Bridging runtime and source context

For too long, runtime security and static analysis have operated in separate universes. Sysdig’s runtime threat detection, powered by Falco, provides unparalleled runtime context: process activity, network connections, and file system interactions within live containers. Meanwhile, Semgrep provides the source context: the repositories, dependency manifests, and code ownership that represent the ground truth for your developers.

The problem has always been the manual correlation required to bridge them. A security engineer gets a finding from Sysdig about a critical in-use vulnerability in a production pod but then has to manually hunt for the source repository. A developer gets a software composition analysis (SCA) finding from Semgrep but has no data to determine if it's a theoretical risk or a five-alarm fire in production.

This integration replaces that manual hunt with a dynamic, automated data enrichment process.

Anatomy of an enriched finding: The data flow

When a Sysdig finding is generated, a precise, automated workflow is triggered to fuse runtime and source context.

  1. Runtime Detection: Sysdig detects a vulnerable package being used by a running process inside a container. This generates a detailed runtime finding, for example,  including the image ID, package name (log4j-core), and version (2.14.1).
  2. Metadata Extraction: As part of its standard data collection, Sysdig has already collected the container image's metadata, including the OCI labels for the source repository and commit SHA.
  3. The Enrichment: Sysdig uses this extracted source information to match data to the Semgrep platform. The query essentially asks: "For the repository github.com/my-org/my-app at commit a1b2c3d, what do you know about the package log4j-core?"
  4. Source Context Retrieval: Because Semgrep has already scanned this, it has the required data indexed. It instantly returns a payload containing the precise location of the vulnerable dependency (e.g., pom.xml, line 52) and the remediation advice (e.g., "Upgrade to version 2.17.1").
  5. Unified Finding: Sysdig merges this Semgrep payload into its original runtime finding. The security engineer now sees a single, actionable view in the Sysdig Secure UI, containing both the "what" and the "where." Whilst within Semgrep, can see this vulnerability with the runtime context.

It’s a direct, programmatic path from a runtime event to a source code location.

How it works: Building the metadata bridge

The bridge between runtime and source isn't magic - it's built on a simple and powerful DevOps best practice that you enable in your CI/CD pipeline: embedding metadata directly into the container image. This one-time setup creates a durable link that travels with your application from source to production.

This is done using standard Open Container Initiative (OCI) labels. By adding these key-value pairs, you create the permanent breadcrumb trail that connects a running workload back to its origin. This is a robust, non-proprietary mechanism. For this integration, two labels are most important:

  • org.opencontainers.image.source: The URL of the source code repository.
  • org.opencontainers.image.revision: The specific commit hash (SHA) from which the image was built.

Implementing this is a straightforward modification to your image build step in any CI/CD system. 

Once an image built this way is deployed, Sysdig automatically discovers these labels. The embedded repository and commit information now serve as the exact coordinates for matching the data to Semgrep, closing the loop.

The result: A single, actionable view

This integration fundamentally changes the nature of a security finding. Instead of a simple notification, teams get a comprehensive remediation ticket in a single view.

By building a seamless technical bridge between runtime and source code, Sysdig and Semgrep are giving teams a unified signal. This allows security operations to reduce alert fatigue and focus on high-impact threats, while developers receive the precise, actionable data needed to reduce Mean Time to Remediation (MTTR). We’re empowering you to move from security bottlenecks to secure velocity, finally delivering on the promise of DevSecOps