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Is half your workforce breaking AI policy? | The AI Insider Threat Report

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14 Jan 2025

Information Leakage

Information Leakage

Information Leakage

Information leakage occurs when sensitive or confidential data is unintentionally exposed or accessed by unauthorized parties due to weaknesses in security controls, poor data management, or misconfigurations. This can happen in various contexts, including software vulnerabilities, system misconfigurations, or insecure communication channels. Information leakage can lead to data breaches, unauthorized access, and exploitation of critical information. Common Causes of Information Leakage:
  • Misconfigured Cloud Storage: Exposing sensitive files or databases by failing to apply proper access controls.
  • Error Messages: Detailed error logs that reveal system paths, database structures, or other internal information to external users.
  • Hard-Coded Secrets: Embedding sensitive information such as API keys, credentials, or tokens directly into source code that may be publicly accessible.
  • Metadata Exposure: Exposing hidden data in files (such as author details or revision history in documents) that reveals sensitive insights.
  • Prompt Injection: Manipulating AI system prompts to trick the system into disclosing confidential data or bypassing security restrictions.
Impact of Information Leakage:
  • Security Vulnerabilities: Exposing system details that attackers can use to identify entry points for further exploitation.
  • Privacy Violations: Unauthorized exposure of personal identifiable information (PII) or confidential business data.
  • Reputational Damage: Loss of trust from customers, clients, and stakeholders due to perceived negligence.
  • Financial Loss: Costs associated with regulatory fines, legal fees, and damage control after a data breach.
Information leakage can occur at any stage of data handling, making comprehensive data governance, secure development practices, and regular audits essential to mitigate risks.

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