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FIRST LOOK OpenAI Expands ChatGPT Into Family and Caregiver Households // FIRST LOOK Iroh Launches Mesh LLM for Distributed AI Across Peer Nodes // HIGH HalluSquatting Exploits AI Hallucinations for Botnet RCE // CRITICAL OpenClaw AI Assistant Flaws Enable WhatsApp-to-Host RCE // FIRST LOOK Netwrix Analysis: AI Agents Widen the Non-Human Identity Gap // FIRST LOOK Ghostcommit PoC Embeds Prompt Injection in PNG to Steal Repo Secrets // FIRST LOOK Microsoft MDASH Brings AI-Powered Windows Vulnerability Discovery // FIRST LOOK FableCut Ships AI-Drivable Browser Video Editor via MCP and REST // FIRST LOOK AI Agents Emerge as a New Identity Class Orgs Must Secure // HIGH CVE-2026-12958: GhostApproval Symlink Attack on Coding Agents //
GCP

Gcp

3 reports
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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.

Vertex AI Privilege Escalation Exposes GCP Credentials

Vertex AI Privilege Escalation Exposes GCP Credentials

ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 9.2 Palo Alto Unit 42

Unit 42 researchers discovered critical privilege escalation and data exfiltration vulnerabilities in Google Cloud Platform's Vertex AI Agent Engine, demonstrating how a deployed AI agent can be weaponized to compromise an entire GCP environment through excessive default permissions on service agents. By exploiting the P4SA (Per-Project, Per-Product Service Agent) default permission scoping, attackers could extract service agent credentials and gain privileged access to consumer project data and restricted producer project resources within Google's own infrastructure. Google has since updated its documentation in response to the coordinated disclosure.

Google Vertex AI Over-Privilege Enables Data Exfiltration

Google Vertex AI Over-Privilege Enables Data Exfiltration

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.5 Dark Reading

Palo Alto Networks researchers have identified over-privilege vulnerabilities in Google's Vertex AI platform, demonstrating how malicious actors could exploit AI agents to exfiltrate sensitive data and pivot into restricted cloud infrastructure. The findings highlight systemic risks in agentic AI deployments where excessive permissions granted to AI workloads expand the attack surface beyond traditional cloud security boundaries. This research underscores the growing urgency around securing AI agent permissions and enforcing least-privilege principles in enterprise ML platforms.

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