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UNIT-42

Unit-42

2 reports
All LLM Security Agentic AI Industry News Research Supply Chain Prompt Injection First Look: Security Regulatory Adversarial ML Jailbreaks Model Theft Data Poisoning AI Security Tools Security Operations
Vertex AI SDK Bucket Squatting Flaw Enables Model Hijack

Vertex AI SDK Bucket Squatting Flaw Enables Model Hijack

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.5 The Hacker News

A vulnerability in the Google Cloud Vertex AI Python SDK allowed unauthenticated attackers to intercept model uploads by pre-registering predictable staging bucket names — a technique Unit 42 calls 'Pickle in the Middle'. Once a malicious model replaced the legitimate upload, arbitrary code executed inside Google's serving infrastructure via pickle deserialization. Google patched the flaw in v1.148.0 after disclosure in March 2026, but the incident highlights systemic risks in ML pipeline supply chains.

Zealot: Autonomous LLM Cloud Penetration Testing System

Zealot: Autonomous LLM Cloud Penetration Testing System

ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 9.0 Palo Alto Unit 42

Unit 42 researchers built 'Zealot,' a multi-agent LLM-powered penetration testing system capable of autonomously executing end-to-end offensive operations against cloud infrastructure, demonstrating that AI acts as a significant force multiplier for cloud attacks. The system successfully attacked a misconfigured GCP sandbox environment using a supervisor-coordinated architecture of specialist agents, validating that agentic AI can operate at machine speed against real cloud misconfigurations. This research follows Anthropic's November 2025 disclosure of a state-sponsored AI-orchestrated espionage campaign and marks a critical inflection point in understanding autonomous AI offensive capabilities.

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