Slack AI Vulnerability Exposes Private Channels to Potential Data Theft via 'Prompt Injection'

August 22, 2024
Slack AI Vulnerability Exposes Private Channels to Potential Data Theft via 'Prompt Injection'
  • A significant vulnerability in Slack's AI has been identified, allowing attackers to potentially steal sensitive information from private channels by manipulating the AI's language model.

  • This manipulation can occur through a technique known as 'prompt injection,' which can be used to create phishing links targeting users.

  • The implications of this vulnerability are serious, as sensitive data is often shared on Slack, necessitating user awareness and potential adjustments to privacy settings.

  • Slack's response to the issue suggests a lack of understanding regarding the nature and severity of the vulnerability.

  • A spokesperson from Salesforce, Slack's parent company, stated that they have addressed the issue but did not provide specific details about the measures taken.

  • The exploit significantly increases the attack surface, as attackers do not need to be present in Slack to initiate the attack.

  • Malicious instructions hidden in uploaded files, such as PDFs, can lead to similar attacks, allowing for data theft without direct user participation.

  • Users are advised to review the AI policies of applications they frequently use to ensure their security and mitigate potential risks.

  • PromptArmor has emphasized that this example illustrates a broader risk involving multiple opportunities for attackers to exploit prompt injection vulnerabilities.

  • PromptArmor, the security firm that disclosed the vulnerability, highlighted the potential for unauthorized data access in private channels where the attacker is not a member.

  • The AI system has been found to intentionally access private direct messages and file uploads, raising further security concerns.

  • Despite the serious nature of these findings, Slack has not publicly commented on the vulnerabilities reported by PromptArmor.

Summary based on 10 sources


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