A security researcher at Adversa identified a vulnerability in Grok that allows attackers to steal user information by encrypting harmful instructions. The attack works by hiding malicious commands in ciphertext alongside decryption keys and instructions, which the AI system then processes without triggering its safety filters.
When users instruct Grok to summarize a webpage containing encrypted content, the system decrypts the hidden instructions and executes them. The decrypted commands direct Grok to construct what appears to be a decryption key but is actually the user’s name, location, and chat history. This data is then appended to a URL and transmitted to an attacker’s server, where it is logged.
Researchers theorize that Grok’s filtering guardrails inspect text entering and leaving the model but do not monitor the output of the model’s own code execution. Because instructions to decrypt content using PBKDF2 and AES-256-GCM appear as ordinary requests, they pass through content classifiers. Once decrypted within the model’s execution sandbox, the actual harmful instructions reach the system as its own tool output, bypassing the guardrails entirely.
Adversa employed a similar technique against Google’s Gemini, successfully prompting the system to generate restricted content including instructions for building weapons and reproducing its system instructions. The vulnerability in Grok remained exploitable at the time of publication, despite xAI being notified in June. The technique, termed Cryptographic Context Injection, represents a broader attack category targeting the wider context an LLM processes beyond traditional prompt inputs, including tool outputs and runtime results.
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