text code block:from logs-aws_bedrock.invocation-* // keep token usage data | keep user.id, gen_ai.usage.prompt_tokens, gen_ai.usage.completion_tokens // Aggregate usage metrics | stats Esql.ml_usage_prompt_tokens_max = max(gen_ai.usage.prompt_tokens), Esql.ml_invocations_total_count = count(*), Esql.ml_usage_completion_tokens_avg = avg(gen_ai.usage.completion_tokens) by user.id // Filter for suspicious usage patterns | where Esql.ml_usage_prompt_tokens_max > 5000 and Esql.ml_invocations_total_count > 10 and Esql.ml_usage_completion_tokens_avg > 500 // Calculate a custom risk factor | eval Esql.ml_risk_score = (Esql.ml_usage_prompt_tokens_max / 1000) * Esql.ml_invocations_total_count * (Esql.ml_usage_completion_tokens_avg / 500) // Filter on risk score | where Esql.ml_risk_score > 10 // sort high risk users to top | sort Esql.ml_risk_score desc
Install detection rules in Elastic Security
Detect Potential Abuse of Resources by High Token Count and Large Response Sizes in the Elastic Security detection engine by installing this rule into your Elastic Stack.
To setup this rule, check out the installation guide for Prebuilt Security Detection Rules(external, opens in a new tab or window).