What happened?

Prompt injection has been identified by many independent sources as one of the most effective and widespread attack vectors in 2025 and 2026. CrowdStrike's 2026 Global Threat Report documented that such attacks occurred in over 90 organizations in 2025, and these attacks were used to steal credentials and cryptocurrency. Real-world examples demonstrate how such vulnerabilities have been exploited in systems like Slack AI.

Why is it important?

Prompt injection directly threatens the security of LLM systems used by businesses. Such attacks can lead to unauthorized actions in critical areas like customer service and automation systems, data breaches of sensitive information, and disruptions in internal workflows. Particularly, the trust in LLMs for automated structures opens a door for cybercriminals. For instance, the leakage of malicious information through RAG (retrieval-augmented generation) lines increases the vulnerabilities of such systems. Actors conducting high-level cyber attacks are becoming more sophisticated with these new attack techniques, making it imperative for businesses to rethink their security strategies.

Attack TypeDescriptionExample Case
Prompt InjectionMalicious instructions sent by the user to LLMSlack AI vulnerability
Model Steering ManipulationTargeting weak modelsMicrosoft 365 Copilot attack
Memory PoisoningAdding harmful instructions to long-term memory-

Measures that can be taken against such attacks include restricting model permissions, segmenting unreliable content, and monitoring internal workflows. Businesses should strengthen their security strategies by viewing LLMs not only as powerful tools but also as potential threats.

What's next?

In the future, the security of LLM-based systems will gain more importance. Businesses will need to continuously follow up-to-date security practices to protect user data and enhance the reliability of automated systems. Additionally, considering the evolution of cyber threats, organizations should reassess their expectations from LLMs and develop strategies to address security vulnerabilities.

In conclusion, prompt injection stands out as a vulnerability that exploits the fundamental operating logic of AI systems. It is crucial for businesses to abandon the habit of viewing LLMs as reliable decision-makers and start evaluating these systems as potential threats.