« AWS Bedrock Model Invocation Logging Disabled or Modified AWS Bedrock Provisioned Model Throughput Tampering »
Elastic Docs ›Elastic Security [8.19] ›Detections and alerts ›Prebuilt rule reference

AWS Bedrock Model Prompt or Completion Containing Credentials

edit
IMPORTANT: This documentation is no longer updated. Refer to Elastic's version policy and the latest documentation.

AWS Bedrock Model Prompt or Completion Containing Credentials

edit

Identifies an Amazon Bedrock model invocation whose prompt or completion contains an AWS access key identifier (AKIA long-term or ASIA temporary/STS, followed by 16 characters), an Amazon Bedrock API key (ABSK bearer token), or a PEM private-key block. Credentials in the model input mean an application or user is sending secrets to the model, exposing them to invocation logging, the model provider, and prompt history; credentials in the model output mean the model is emitting secrets, which can result from training-data leakage, poisoned context, or a prompt-injection-driven exfiltration attempt. Either case is a credential-exposure event that warrants immediate rotation of the affected secret.

Rule type: esql

Rule indices: None

Severity: medium

Risk score: 47

Runs every: 10m

Searches indices from: now-60m (Date Math format, see also Additional look-back time)

Maximum alerts per execution: 100

References:

Tags:

  • Domain: LLM
  • Data Source: AWS Bedrock
  • Data Source: Amazon Web Services
  • Use Case: Threat Detection
  • Mitre Atlas: LLM06
  • Resources: Investigation Guide
  • Tactic: Credential Access

Version: 1

Rule authors:

  • Elastic

Rule license: Elastic License v2

Investigation guide

edit

Triage and analysis

Investigating AWS Bedrock Model Prompt or Completion Containing Credentials

Bedrock model invocation logging records the full request and response of each InvokeModel/Converse call. This rule scans the decoded prompt and completion for live-credential patterns: AWS access key IDs (AKIA/ASIA followed by 16 characters) and PEM private-key headers. A credential in the prompt indicates secrets are being sent to the model (and persisted in logs and, for hosted models, to the provider); a credential in the completion indicates the model returned a secret, which is a sign of training-data or context leakage or a successful prompt-injection exfiltration.

Possible investigation steps

  • Review the matched value in "gen_ai.prompt" and "gen_ai.completion" and confirm whether it is a live credential or an example/placeholder.
  • Identify the caller in "user.id" and the model in "aws_bedrock.invocation.model_id", and determine which application generated the invocation.
  • If the credential is in the completion, review the prompt for injection or data-exfiltration instructions and check the model’s knowledge base or context sources.
  • Determine the scope and privileges of the exposed credential to gauge impact.

False positive analysis

  • Example or documentation keys (such as the AWS EXAMPLE key) match the pattern. Confirm the value is a real credential before escalating.

Response and remediation

  • If the credential is live, rotate or deactivate it immediately and review CloudTrail for any use of it.
  • Identify and fix the application path that placed the credential into the prompt, and add input/output filtering (such as a Bedrock guardrail with a sensitive-information policy) to prevent recurrence.

Setup

edit

This rule requires Amazon Bedrock model invocation logs ingested via the Elastic AWS Bedrock integration, with text data delivery enabled in the Bedrock model-invocation-logging configuration.

Rule query

edit
from logs-aws_bedrock.invocation-* metadata _id, _version, _index
| where event.action in ("ConverseStream", "Converse") AND
   ( gen_ai.prompt rlike """.*(AKIA|ASIA)[A-Z0-9]{16}.*"""
    or gen_ai.completion rlike """.*(AKIA|ASIA)[A-Z0-9]{16}.*"""
    or gen_ai.prompt rlike """.*-----BEGIN [A-Z ]*PRIVATE KEY-----.*"""
    or gen_ai.completion rlike """.*-----BEGIN [A-Z ]*PRIVATE KEY-----.*"""
    or gen_ai.prompt rlike """.*ABSK[A-Za-z0-9+/=]{20}.*"""
    or gen_ai.completion rlike """.*ABSK[A-Za-z0-9+/=]{20}.*"""
    or gen_ai.prompt rlike """.*gh[pousr]_[A-Za-z0-9]{36}.*"""
    or gen_ai.completion rlike """.*gh[pousr]_[A-Za-z0-9]{36}.*"""
    or gen_ai.prompt rlike """.*github_pat_[A-Za-z0-9_]+.*"""
    or gen_ai.completion rlike """.*github_pat_[A-Za-z0-9_]+.*"""
    or gen_ai.prompt rlike """.*glpat-[A-Za-z0-9_\\-]+.*"""
    or gen_ai.completion rlike """.*glpat-[A-Za-z0-9_\\-]+.*""")
| keep _id, _version, _index, @timestamp, gen_ai.*, aws_bedrock.*, user.*, cloud.*, event.*

Framework: MITRE ATT&CKTM

« AWS Bedrock Model Invocation Logging Disabled or Modified AWS Bedrock Provisioned Model Throughput Tampering »