Malicious npm packages, pypi malicious packages, and other forms of malicious code continue to infiltrate open-source ecosystems. The Malicious Code Digest is Xygeni’s weekly malware report that tracks and verifies new threats in the software supply chain, including confirmed backdoors, trojans, and spyware spreading through registries like npm and PyPI.
Our research team updates this page weekly with the latest indicators of compromise (IOCs), technical breakdowns, and real-world exploit patterns. Developers, AppSec leads, and security engineers can use this digest to stay ahead of npm malware and pypi malware campaigns targeting CI/CD environments.
Important note:
this list does not include the packages affected by the second wave of the Shai Hulud npm supply chain attack. You can find the full breakdown of that campaign, along with all impacted packages, in our dedicated analysis:
Weekly Summary: November 28 – December 5, 2025
Researchers confirmed 146 new malicious packages across npm and PyPI during this period, marking one of the most active weeks of the quarter.
Key highlights
- 1. Large-scale automated publishing dominates
Attackers relied heavily on scripted pipelines, producing massive clusters with sequential versions and identical metadata.
The biggest families this week include:
elf-stats* (más de 70 variantes), x402-legacy, liblynxtextra.so, libdebugrouter.so, chain-selectors, sd-notexsit, karem*, phx-core*.
All show clear automation fingerprints. - 2. DevTools impersonation increases sharply
Multiple malicious packages mimicked widely used developer tools in order to infiltrate CI/CD environments, including:
tailwind-state, tailwindcss-forms, codemirror-5, eslint-plugin-react-hooks-published, vitest-environment-jsdom-patched, remark-parse10, hast-util-to-mdast9, umap-wasm. - 3. Version-inflation and extreme numbering used to evade detection
Packages such as node-calculator-x7k9-evil:9999.9.9999, sd-notexsit:999.x versions, browser-client-neptune:99.99.x, and several elf-stats variants used exaggerated versioning to bypass heuristics and appear internally versioned. - 4. Financial, crypto, and gaming themes reappear
Malware families targeted workflows that commonly run inside developer or automation systems:
btc-transaction-helper, chia-gaming-lobby-connection, vault-watcher, phx-core*, bfui-dsm-react-ui, wfui-dbd-react-ui. - 5. PyPI activity spikes again
After weeks of npm-only attacks, PyPI saw new confirmations, including:
discord-selfsbotsx, mzip, minizip, aiogram-msgeffect, zakuchienne, mongland, rtcpy, pyrtp, aounitaounit2. - 6. Seasonal / obfuscation naming trend emerges
A large portion of the week’s malware used “holiday-safe” naming to appear harmless:
elf-stats-starlit-mitten, elf-stats-fuzzy-sparkler, elf-stats-gingersnap-ornament, elf-stats-evergreen-nightcap, etc.
Despite playful names, all follow the same coordinated malicious pattern.
View the full montly malware report →
Monthly Malware Report: Confirmed Malicious npm Packages in October 2025
In November 2025, Xygeni analyzed and reported more than 260 malicious packages across npm and PyPI. This monthly report includes all confirmed malicious npm and PyPI packages for the month, including those discovered during the final week.
| Ecosystem | Package | Date |
|---|---|---|
| npm | @rajank18/smart-commit:1.0.0 | Nov 24, 2025 |
| npm | eslint-plugin-whatever:9.0.1 | Nov 23, 2025 |
| npm | ccs-react-lib:7.7.8 | Nov 23, 2025 |
| npm | humhub:5.0.3 | Nov 23, 2025 |
| npm | humhub:5.0.6 | Nov 23, 2025 |
| npm | across-toolkit:9.0.1 | Nov 23, 2025 |
| npm | flaresdsdsdsdsd:45.0.0 | Nov 23, 2025 |
| npm | @secretcollect/identity-core:6.0.0 | Nov 23, 2025 |
| npm | startupkit-umbraco-webpack:2.0.0 | Nov 23, 2025 |
| npm | telstraprogrammablenetworkapilib:2.9.1 | Nov 23, 2025 |
How We Detect Malicious Code in npm Malware and PyPI Malware
Xygeni uses multi-layered techniques to stop malicious code before it spreads. First of all, static code analysis detects obfuscation patterns, hidden payloads, and script abuse. In addition, behavioral sandboxing analyzes install hooks, runtime commands, and persistence tricks. Moreover, machine learning detection identifies zero-day npm malware and pypi malware variants missed by signature scanners. Finally, the Early Warning System monitors public repositories in real time, validates findings, and alerts DevOps teams immediately.
As a result, this combination ensures developers receive fast, actionable intelligence integrated directly into CI/CD workflows.
Why Developers Should Care About Malicious npm Packages
Modern threats rarely wait for runtime. For example, malicious npm packages often execute during installation, while pypi malicious packages hide token exfiltration or backdoors. Attackers:
- Flip private GitHub repos to public to replicate them.
- Exfiltrate credentials and secrets using encoded payloads.
- Use obfuscated JavaScript loaders to deploy ransomware or botnets.
In fact, malicious open-source packages surged 156% in one year. Therefore, teams that rely only on delayed feeds or basic scanners fall behind.
What This Malware Report Tracks in npm and PyPI
This digest is the central hub for:
- Confirmed malicious npm packages
- Confirmed pypi malicious packages
- Behavior-based detections of malicious code
- Registry-confirmed incidents
- Weekly and monthly malware report summaries
- Historical changelog of all npm malware and pypi malware findings
In other words, it provides a single point of reference. The research team at Xygeni updates this page weekly with links to full technical analyses and GitHub IOCs.
How to Protect Against Malicious npm Packages and PyPI Malware
Because of this growing risk, organizations need more than basic dependency checks. Strong defenses against malicious npm packages and pypi malicious packages require both preventive controls and runtime enforcement:
Enforce Lockfile-Only Installs Against Malicious npm Packages
Use npm ci or pip install --require-hashes in CI/CD.
This ensures the exact dependency tree defined in lockfiles is used. As a result, attackers cannot slip in modified or typosquatted versions of malicious npm packages.
Pre-Install Scanning for npm Malware and PyPI Malware
Integrate Xygeni’s Early Warning Engine to scan npm malware and pypi malware before packages reach your environment.
Moreover, detect suspicious postinstall scripts, obfuscated loaders, or hardcoded C2 URLs.
Guardrails to Block Builds with Malicious Code
Set guardrails to fail builds automatically if confirmed malicious npm packages or pypi malicious packages are detected.
For example, break builds on packages with unpublished maintainers, obfuscation patterns, or IOC matches. Consequently, malicious code never passes unnoticed.
Generate and Validate SBOMs Against Malicious npm Packages and PyPI Malware
Create SBOMs (CycloneDX, SPDX) for every build.
Afterward, compare against known malicious npm packages and pypi malware feeds to track both direct and transitive dependencies.
Credential and Token Protection from npm Malware and PyPI Malware
Many malicious npm packages try to read .npmrc, .pypirc, or environment variables.
Therefore, run builds in hardened containers with minimal secrets exposed. Additionally, use secrets managers instead of environment variables to block malicious code abuse.
Monitor Registry and Maintainer Changes in Malicious npm Packages
Attackers often hijack abandoned projects.
In particular, watch for sudden maintainer swaps, unusual versioning jumps, or excessive publishes in npm malware and pypi malicious packages.
Developer Training on Detecting Malicious Code in npm and PyPI
Teach teams to spot red flags such as:
- Package names with typos (
reqeustinstead ofrequest). - Unusual
installorpreparescripts. - Recently created packages with suspiciously high version numbers.
Above all, this awareness helps detect malicious code early.
Runtime Anomaly Detection for Malicious npm Packages and PyPI Malware
Even if malware bypasses static checks, runtime detection in CI/CD can catch:
- Unexpected network connections.
- File system modifications outside expected directories.
- Persistence attempts across jobs.
Finally, this ensures npm malware and pypi malware threats are stopped even after installation.
By combining these controls, teams prevent malicious npm packages and pypi malicious packages from ever reaching production pipelines.
Try Xygeni’s Malware Detection Tools
Xygeni delivers:
- Real-time detection of malicious code, including backdoors, spyware, and ransomware.
- In contrast to basic scanners, analysis across npm, PyPI, Maven, NuGet, RubyGems, and more.
- Automatic build blocking when the malware report identifies risk.
- Exploitability insights, maintainer reputation checks, and anomaly detection.
Stay Informed
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