AWS Bedrock Guardrails Detected Multiple Violations by a Single User Over a Session

  1[metadata]
  2creation_date = "2024/05/02"
  3maturity = "production"
  4updated_date = "2025/07/16"
  5
  6[rule]
  7author = ["Elastic"]
  8description = """
  9Identifies multiple violations of AWS Bedrock guardrails by the same user in the same account over a session. Multiple
 10violations implies that a user may be intentionally attempting to cirvumvent security controls, access sensitive
 11information, or possibly exploit a vulnerability in the system.
 12"""
 13false_positives = ["Legitimate misunderstanding by users or overly strict policies"]
 14from = "now-60m"
 15interval = "10m"
 16language = "esql"
 17license = "Elastic License v2"
 18name = "AWS Bedrock Guardrails Detected Multiple Violations by a Single User Over a Session"
 19note = """## Triage and analysis
 20
 21### Investigating AWS Bedrock Guardrails Detected Multiple Violations by a Single User Over a Session
 22
 23Amazon Bedrock Guardrail is a set of features within Amazon Bedrock designed to help businesses apply robust safety and privacy controls to their generative AI applications.
 24
 25It enables users to set guidelines and filters that manage content quality, relevancy, and adherence to responsible AI practices.
 26
 27Through Guardrail, organizations can define "denied topics" to prevent the model from generating content on specific, undesired subjects,
 28and they can establish thresholds for harmful content categories, including hate speech, violence, or offensive language.
 29
 30#### Possible investigation steps
 31
 32- Identify the user account that caused multiple policy violations over a session and whether it should perform this kind of action.
 33- Investigate the user activity that might indicate a potential brute force attack.
 34- Investigate other alerts associated with the user account during the past 48 hours.
 35- Consider the time of day. If the user is a human (not a program or script), did the activity take place during a normal time of day?
 36- Examine the account's prompts and responses in the last 24 hours.
 37- If you suspect the account has been compromised, scope potentially compromised assets by tracking Amazon Bedrock model access, prompts generated, and responses to the prompts by the account in the last 24 hours.
 38
 39### False positive analysis
 40
 41- Verify the user account that caused multiple policy violations by a single user over session, is not testing any new model deployments or updated compliance policies in Amazon Bedrock guardrails.
 42
 43### Response and remediation
 44
 45- Initiate the incident response process based on the outcome of the triage.
 46- Disable or limit the account during the investigation and response.
 47- Identify the possible impact of the incident and prioritize accordingly; the following actions can help you gain context:
 48    - Identify the account role in the cloud environment.
 49    - Identify if the attacker is moving laterally and compromising other Amazon Bedrock Services.
 50    - Identify any regulatory or legal ramifications related to this activity.
 51- Review the permissions assigned to the implicated user group or role behind these requests to ensure they are authorized and expected to access bedrock and ensure that the least privilege principle is being followed.
 52- Determine the initial vector abused by the attacker and take action to prevent reinfection via the same vector.
 53- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
 54"""
 55references = [
 56    "https://docs.aws.amazon.com/bedrock/latest/userguide/guardrails-components.html",
 57    "https://atlas.mitre.org/techniques/AML.T0051",
 58    "https://atlas.mitre.org/techniques/AML.T0054",
 59    "https://www.elastic.co/security-labs/elastic-advances-llm-security",
 60]
 61risk_score = 47
 62rule_id = "0cd2f3e6-41da-40e6-b28b-466f688f00a6"
 63setup = """## Setup
 64
 65This rule requires that guardrails are configured in AWS Bedrock. For more information, see the AWS Bedrock documentation:
 66
 67https://docs.aws.amazon.com/bedrock/latest/userguide/guardrails-create.html
 68"""
 69severity = "medium"
 70tags = [
 71    "Domain: LLM",
 72    "Data Source: AWS Bedrock",
 73    "Data Source: AWS S3",
 74    "Resources: Investigation Guide",
 75    "Use Case: Policy Violation",
 76    "Mitre Atlas: T0051",
 77    "Mitre Atlas: T0054",
 78]
 79timestamp_override = "event.ingested"
 80type = "esql"
 81
 82query = '''
 83from logs-aws_bedrock.invocation-*
 84
 85// Filter for compliance violations detected
 86| where gen_ai.compliance.violation_detected
 87
 88// keep relevant ECS + model fields
 89| keep
 90  user.id,
 91  gen_ai.request.model.id,
 92  cloud.account.id
 93
 94// count violations by user, model, and account
 95| stats
 96    Esql.ml_violations_count = count(*)
 97  by
 98    user.id,
 99    gen_ai.request.model.id,
100    cloud.account.id
101
102// Filter for repeated violations
103| where Esql.ml_violations_count > 1
104
105// sort descending by violation volume
106| sort Esql.ml_violations_count desc
107'''