AWS Bedrock allows developers to build AI-powered applications by connecting foundation models to enterprise data and infrastructure. However, researchers from XM Cyber have identified eight critical attack vectors that exploit these connections. These threats target the permissions and integrations surrounding the AI models, such as S3 buckets and Lambda functions, rather than the models themselves.
The identified vulnerabilities include log manipulation to hide malicious activity, hijacking autonomous agents to perform unauthorized tasks, and poisoning managed prompts to subvert AI behavior at scale. Other vectors focus on compromising knowledge bases to exfiltrate proprietary data or move laterally into systems like Active Directory. To secure Bedrock environments, security teams must move beyond model-centric defenses and focus on mapping attack paths and enforcing strict IAM controls across the entire AI stack.
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