AWS Bedrock Claude Cross Region Possible Inference Abuse
Description
This detection identifies potential cross-region inference abuse in AWS Bedrock Claude models. Cross-region inference abuse may indicate attempts to bypass regional restrictions, exfiltrate data, or perform unauthorized actions across different AWS regions.
Query · spl
`aws_bedrock_claude` | rename "identity.arn" AS user_arn | rename "input.inputTokenCount" AS input_tokens | rename "output.outputTokenCount" AS output_tokens | rex field=user_arn "assumed-role/[^/]+/(?<user>[^\"]+)$" | rex field="input.inputBodyJson.metadata.user_id" "(?<session_user>user_[^_]+.*)" | eval input_tokens=tonumber(input_tokens) | eval output_tokens=tonumber(output_tokens) | eval token_ratio=round(output_tokens / max(input_tokens,1), 2) | eval model_short=replace(modelId,"^.*/","") | eval mismatch_detail=region." -> ".inferenceRegion | where isnotnull(user_arn) AND len(user_arn)>10 | where isnotnull(session_user) | where region!=inferenceRegion | where input_tokens>=2000 | table _time, user, user_arn, session_user, model_short, input_tokens, output_tokens, token_ratio, mismatch_detail, operation, host | sort - input_tokens | `aws_bedrock_claude_cross_region_possible_inference_abuse_filter`
Implementation guide
You must install and configure the Splunk Add-on for AWS (https://splunkbase.splunk.com/app/1876). Enable Amazon Bedrock model invocation logging in AWS so that Claude request/response payloads are delivered to S3 and/or CloudWatch Logs (see https://docs.aws.amazon.com/bedrock/latest/userguide/model-invocation-logging.html for setup steps), then ingest those logs into Splunk via the AWS TA. Configure the aws_bedrock_claude macro to point to the index and sourcetype (json_no_timestamp) where these logs land.
Known false positives
- False positives may arise from legitimate use cases where users are accessing AWS Bedrock Claude models across different regions for valid reasons, such as multi-region deployments, testing, or development purposes. It is important to review the context of the detected events to determine if they represent actual abuse or benign usage.
Analyst notes
Known false positives: False positives may arise from legitimate use cases where users are accessing AWS Bedrock Claude models across different regions for valid reasons, such as multi-region deployments, testing, or development purposes. It is important to review the context of the detected events to determine if they represent actual abuse or benign usage.