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2024 Sonatype Blog

The Hugging Face Incident Changes the Vulnerability Equation What Is Grounding? Why AI Coding Assistants Need Better Intelligence Open Source, Open Infrastructure, and the Space Between Request for Comments: CARE and Maven Central AI Is Forcing a New Open Source Security Model Vulnerability Prioritization Is Missing the AI-Era Point The Hidden National Security Threat Inside AI-Driven Software Miasma Returns: Leo Platform Compromise in npm The Rise of Collective Defense for Open Source Signal Over Noise: Reachability Analysis Is the Reality Check SCA Has Been Missing Software Security Has to Start at Assembly easy-day-js Targets Mastra, Dependency Attacks Grow Open Publishing, Commercial Scale Software Dependency Cooldowns Are a Symptom, Not a Strategy Atomic Arch npm Campaign Adds Malicious Dependency From SBOMs to AI BOMs: Why SPDX 3.0 Matters Mythos Found 10,000 Vulnerabilities. The Bigger Challenge Is Fixing Them New Shai-Hulud Miasma Wave Hits Hundreds of npm Packages Lazarus Group's Latest: Brandjacking Campaign on npm 5 Steps to Turn Your RMF Backlog Into a Continuous ATO: The CSRMC Migration Playbook The AI Race Is Becoming a Remediation Race Red Hat Cloud Services npm Packages Hijacked Inside a 176-Package npm Campaign Built to Beat Your Internal Dependencies AI Is Making Software Autonomous, and Governance Must Follow Your Outdated Repository Still Works, But It May Not Be Safe Hijacked npm Package Attempts to Deliver PolinRider-Linked RAT AppSec Tools Explained: SAST vs SCA vs DAST | Sonatype Managing Open Source Software Risks With the HeroDevs EOL Dashboard Shai-Hulud is Back: Maintainer Accounts Are Still the Soft Target Building Trusted AI Development With Kiro and Sonatype Guide How to Build a Software Supply Chain Security Playbook The Evolution of Open Source Malware: From Volume to Trust Abuse The Mythos AI Vulnerability Storm: What to Do Next Malicious PyTorch Lightning Packages Found on PyPI Why Developer Experience Is the Foundation of DevSecOps Success Open is Not Costless: Reclaiming Sustainable Infrastructure Q1 Updates in Nexus Repository: More Formats, Stronger Operations, and a Better Day-to-Day Experience Self-Propagating npm Malware Turns Trusted Packages Into Attack Paths The Time Is Now to Prepare for CRA Enforcement Sonatype Innovate: Real Peer Connections, Real Product Influence, Real Recognition Mythos and the AI Vulnerability Storm: Exploring the Control Point When AI Writes Code, Who Governs the Dependencies? Why Software Supply Chain Security Requires a New Playbook Q1 2026 Open Source Malware Index: Adaptive Attacks Exploit Trust Modernizing Nexus Repository: Moving Beyond OrientDB AI, DevSecOps, and the Future of Application Security: The Gartner® Report How Sonatype's Container Scanning Protects You From Zero-Days Axios Compromise on npm Introduces Hidden Malicious Package Is Your Repository Ready for What's Next? Autonomous Development and AI: Speed vs. Security Grounded Intelligence Ensures Safe AI Software Development Compromised litellm PyPI Package Delivers Multi-Stage Credential Stealer Golden Pull Requests: Automating Trusted Remediation Without Breaking Builds Sonatype Discovers Two Malicious npm Packages
Q2 2026 Open Source Malware Index
Sonatype Research Team · 2026-07-09 · via 2024 Sonatype Blog

TL;DR

  • At the end of Q2 2026, Sonatype Research reached 1.8 million malicious packages logged.

  • In Q2, npm accounted for 96.6% of malicious package counts, with repository abuse and trojan-class activity showing how attackers continue to exploit high-trust, high-automation ecosystems.

  • The quarter's defining theme was trust under pressure. Large-scale repository abuse campaigns, worm-like malware, dependency confusion, and maintainer compromises turned trusted software distribution channels into attack paths.

  • Q2 showed attackers evolving beyond obvious malicious packages to target trusted developer workflows through campaigns like Shai-Hulud Miasma, CanisterSprawl, Atomic Arch, malicious PyTorch Lightning releases, dependency confusion, and maintainer/package hijacking.


In Q2 2026, Sonatype Research reached more than 1.8 million malicious packages logged across ecosystems over the past decade. This quarter's malicious activity was driven overwhelmingly by npm, which accounted for 96.6% of packages.

This quarter was not shaped primarily by isolated malicious uploads, but rather a more industrialized pattern of abuse, for example:

  • Large-scale package publication

  • Repository misuse

  • Trojan-class malware operating at massive volumes

npm's dominance should not flatten the story. Sonatype also observed lower-volume but higher-signal malicious behavior across PyPI, NuGet, Hugging Face models, RubyGems, Go, Cargo, and other ecosystems. So, npm produced the flood, but the broader ecosystem showed how attackers continue to probe trusted developer workflows.

Q2 pushed a Q1 trend even further: open source malware is no longer only a package-by-package detection problem. Defenders must understand how malicious packages behave, where they execute, and which trust relationships they abuse.

Infographic - Rolling Malware Index Data - Q2 - 2026

npm Dominated, But Trust Was the Target

npm dominated Q2 by count, but outside npm, the threat landscape became far more concentrated. Nearly 87% of all non-npm malicious package activity occurred in just two ecosystems: PyPI (48.5%) and NuGet (38.0%). Hugging Face models (6.8%) and RubyGems (3.0%) accounted for much of the remainder.

PyPI and NuGet also carried the highest concentrations of higher-risk behaviors:

Threat Type Quantity in PyPI Quantity in NuGet
Potentially unwanted applications (PUAs) 3,286 3,268
Secrets exfiltration 2,155 1,962
Droppers 1,326 676
Host information exfiltration 341 8

While repository abuse and trojan activity drove overall volume, the concentration of exfiltration and payload-delivery behaviors in PyPI and NuGet reinforces that attackers continue to target multiple trusted ecosystems — not just npm.

Trojan activity shows the payload problem. Brandjacking and hijacking show the trust problem. Q2 illustrated both as attackers used npm's reach, familiar package names, compromised maintainers, and dependency relationships to turn trusted paths into attack paths.

The Quarter's Defining Pattern: Trusted Paths Became Attack Paths

The Q2 dataset is reinforced by the quarter's malware research. Sonatype Research published extensively on campaigns that abused trusted packages, maintainers, dependency relationships, and install-time workflows.

Instead of analyzing each campaign in isolation, let's organize them according to the broader patterns they demonstrate.

Self-Propagating and Maintainer-Focused Malware Continued to Evolve

Shai-Hulud remained one of the clearest examples of attackers turning trusted packages into propagation infrastructure.

In early June, Sonatype Research tracked a new Shai-Hulud Miasma wave affecting hundreds of npm packages. Moving beyond standard installation scripts, the campaign abused binding.gyp to execute during install, allowing it to harvest developer and CI/CD data, steal tokens, validate credentials, and publish more malicious artifacts.

Attackers adapted to defender expectations. If security teams only look for suspicious lifecycle scripts in package.json, attackers will move execution elsewhere.

We also tracked CanisterSprawl, a self-propagating npm malware campaign that stole sensitive data from developer machines and then used hijacked credentials to publish additional compromised packages.

Credential theft is no longer always the end state. In modern open source malware, stolen credentials can become the next distribution mechanism.

Dependency Relationships Became a Delivery Mechanism

Several Q2 campaigns showed attackers abusing the way package managers resolve and install dependencies.

In a 176-package npm campaign leveraging dependency confusion, Sonatype researchers found malicious packages with exceptionally high version numbers designed to win automated resolution races against internal dependencies. The malware host environments, downloaded platform-specific payloads, and harvested environment variables, credentials, CI/CD secrets, and authentication tokens.

The easy-day-js campaign followed a related pattern. Attackers compromised trusted Mastra packages and added a malicious dependency, causing installs of those packages to also install and execute easy-day-js.

Atomic Arch extended this pattern past npm by targeting orphaned Arch User Repository packages. By modifying PKGBUILDs to pull in a malicious npm dependency, the campaign enabled credential harvesting, stealth, anti-debugging, and data exfiltration, ultimately impacting around 1,500 packages across multiple waves.

These campaigns demonstrate that attackers do not always need to convince developers to install obviously malicious packages. Compromising a trusted dependency relationship is enough.

Trusted Packages and Maintainers Remained High-Value Targets

Q2 also showed continued attacker focus on trusted packages and maintainer accounts.

For the PyTorch Lightning incident, Sonatype reported how malicious versions of the popular lightning package were uploaded to PyPI after a publisher account compromise. The malicious versions were designed to steal developer credentials and republish malicious versions of repositories accessible through stolen tokens.

We also reported hijacked Red Hat Cloud Services packages that delivered install-time malware designed to steal credentials, spread through trusted workflows, and expose developer environments.

Another hijacked npm package attempted to deliver malware linked to PolinRider, exposing developer systems, CI/CD pipelines, and credentials.

These incidents show why maintainer and publisher security remains central to open source risk. Once a trusted package or account is compromised, the attacker inherits legitimacy.

Brandjacking Remained a Persistent Trust-Abuse Technique

Q2 also included activity associated with Lazarus Group brandjacking on npm. Sonatype reported a campaign involving dozens of packages, some with up to 500 weekly downloads, that used naming and mimicry tactics to appear as though they belonged in legitimate developer environments.

Brandjacking is smaller than trojan activity by raw count in the Q2 dataset, but it remains dangerous because it targets developer assumptions. Attackers mimic naming conventions, ecosystem patterns, organizational signals, and package relationships to get malicious software installed.

The Defender's Challenge: Prioritize Without Being Blinded by Volume

Data and incidents from Q2 2026 illustrate that although the volume of malicious packages is significant, quantity alone cannot function as a proper risk model.

Focusing only on the largest category reduces the quarter to npm repository abuse. Similarly, focusing solely on severe payloads overlooks the automation, trust abuse, and dependency-chain behaviors that enable malicious packages to spread.

Modern open source malware often executes during installation, build, or CI/CD automation rather than waiting for application runtime. Traditional scanning frequently detects artifacts too late — after execution has occurred, secrets are exposed, and follow-on activity is already underway. Consequently, security controls must operate earlier and continuously.

Organizations should:

When Scale Becomes the Threat

Q2 2026 was marked not merely by a rise in malicious packages but a clear demonstration of how open source malware has become industrialized.

Attackers continue to concentrate activity in npm while refining cross-ecosystem techniques. They abuse trusted packages, maintainers, dependencies, and install behaviors, using stolen credentials to compromise victims and propagate through the software supply chain.

While data highlights npm, the actual threat landscape is broader. Attackers exploit systemic trust, automation, and dependency resolution, meaning defenders cannot treat malicious packages as isolated artifacts.

Open source remains a great accelerator of modern software development. But Q2 2026 shows that the same scale that makes open source powerful also makes it attractive to attackers.

When trusted paths become attack paths, security needs to move earlier, faster, and with more context.

Tags

Open Source security research open source malware