A new wave of cyber threats targeting large language models (LLMs) has emerged, exploiting their inherent inability to differentiate between informational content and actionable instructions. Termed >>indirect prompt injection attacks,<< these exploits embed malicious directives within external data sources-such as documents, websites, or emails-that LLMs process during operation. Unlike direct prompt injections, where attackers manipulate [...] The post Indirect Prompt Injection Exploits LLMs' Lack of Informational Context appeared first on GBHackers Security | #1 Globally Trusted Cyber Security News Platform. First seen on gbhackers.com Jump to article: gbhackers.com/indirect-prompt-injection-exploits-llms-lack/
