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Laravel-Lang PHP Packages Compromised to Deliver Cross-Platform Credential Stealer

thehackernews.com 2026-05-23 AI supply chain Critical

What Happened

Cybersecurity researchers have flagged a fresh software supply chain attack campaign that has targeted multiple PHP packages belonging to Laravel-Lang to deliver a comprehensive credential-stealing framework. The affected packages include - laravel-lang/lang laravel-lang/http-statuses laravel-lang/attributes laravel-lang/actions "The timing and pattern of the newly published tags

Why It Matters

The article describes a software supply chain attack in which an attacker with push access to the Laravel-Lang GitHub organization rewrote hundreds of git tags across multiple PHP Composer packages (including laravel-lang/lang, http-statuses, attributes, and actions) to insert a PHP-based, cross-platform credential stealer that auto-loads via Composer.[1][4] Reports from StepSecurity, Aikido Security, and others state that the payload contacts flipboxstudio[.]info, downloads a ~5,900 line stealer, and exfiltrates cloud, CI/CD, browser, password manager, VPN, SSH, and other sensitive secrets from Windows, Linux, and macOS, then deletes itself to hinder forensics.[1][2][3][4] From a CyberSE.AI perspective, this illustrates critical AI supply chain risk: any AI agents, pipelines, or model-training jobs that rely on PHP-based services or CI runners using these packages could have had environment variables, API keys, model access tokens, data connectors, or deployment credentials stolen. Organizations should perform SBOM-driven dependency audits, lock to verified commits, implement strict CI integrity controls (including code signing and tag protection), and run continuous red teaming s

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CyberSE Analysis

This signal maps to AI supply chain. Organizations using AI agents, LLM APIs, SaaS integrations, or sensitive data workflows should review whether this class of issue could create unauthorized tool execution, data leakage, weak approval gates, or unmanaged supply-chain exposure.

Recommended Actions

  • Restrict AI agent tool permissions and production write paths.
  • Review sensitive data access across prompts, logs, embeddings, memory, and SaaS integrations.
  • Add human approval workflows for high-impact or state-changing actions.
  • Run prompt injection and indirect prompt injection tests against affected workflows.
  • Document the owner, control gap, and remediation deadline for this risk class.

Source

https://thehackernews.com/2026/05/laravel-lang-php-packages-compromised.html

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