Researchers discovered vulnerabilities in Google's Python APK that allowed attackers to exploit a trust boundary between two AI agents operating at different privilege levels. The flaw enabled agent-to-agent attack chains capable of triggering automated workflows with supply chain compromise potential. Google has since patched the issues, but the disclosure highlights systemic risks in multi-agent AI architectures.
Google has patched a critical prompt injection vulnerability in an agentic AI tool designed for filesystem operations, where insufficient input sanitisation enabled sandbox escape and arbitrary code execution. The flaw highlights the compounding risk surface of agentic AI systems that interface directly with operating system resources. This is a significant example of how LLM-native vulnerabilities can translate into traditional high-severity RCE outcomes.
Prompt injection vulnerabilities in Salesforce Agentforce and Microsoft Copilot were patched after researchers demonstrated that external attackers could exploit them to exfiltrate sensitive user data. The flaws highlight systemic risks in enterprise AI agent deployments, where insufficient input sanitisation allows malicious content to hijack agent behaviour. Both vendors have issued patches, but the incidents underscore the growing attack surface introduced by agentic AI systems operating with elevated privileges.
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