Encrypted Prompt Injection via AES Obfuscation in Grok and High-Capability LLMs
Security researchers at Adversa, led by Rony Utevsky, have identified a critical vulnerability in high-capability Large Language Models (LLMs), including Grok, involving "cryptographic context injection." This attack method utilizes AES (Advanced Encryption Standard) to obfuscate malicious prompt payloads, bypassing traditional plaintext-based guardrail architectures. By providing both the ciphertext and the decryption key within the same prompt, attackers leverage the model's inherent reasoning and technical capabilities to perform in-context decryption. Once decrypted, the model executes the hidden instructions, rendering current semantic and keyword-based input sanitization methods ineffective against sophisticated cryptographic evasion.