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Introduction:
In today’s cloud-centric world, a single misconfigured permission in an AWS environment can serve as the master key for a complete account takeover. At DEF CON Bahrain’s Cloud Village, researchers demonstrated this threat by deploying a custom, vulnerable AWS lab to showcase the potent offensive capabilities of the PACU exploitation framework. This article reconstructs their methodology, providing a step-by-step guide for understanding how attackers leverage tools like PACU to enumerate identities, escalate privileges, and exploit common cloud security blind spots.
Learning Objectives:
- Understand the core functionality and deployment of the PACU AWS exploitation framework.
- Learn the methodology for enumerating IAM permissions and identifying privilege escalation paths.
- Master practical techniques for exploiting common misconfigurations in AWS services like S3, EC2, and CloudTrail.
1. Setting Up Your Exploitation Environment with PACU
Before hunting for misconfigurations, you need the right tool. PACU is an open-source AWS exploitation framework designed for offensive security testing. It uses a modular system to assist in enumeration, privilege escalation, and data exfiltration.
Step‑by‑step guide explaining what this does and how to use it.
1. Installation: The easiest method is via pip. Ensure you have Python 3.7+ installed and run pip3 install pacu. For an isolated environment, consider using the official Docker image: docker run -it rhinosecuritylabs/pacu:latest.
2. Initial Configuration: On first run, PACU will prompt you to create a new session. Sessions store your AWS keys and collected data. You can create multiple sessions for different assessments.
3. Provisioning Keys: Most PACU modules require AWS access keys. Use the `set_keys` command within a PACU session to configure the Access Key ID and Secret Access Key for your target. These keys could be obtained from compromised application code, public repositories, or other credential leaks.
2. Initial Reconnaissance and Account Discovery
The first step after gaining initial access is to understand your position and the landscape of the cloud account. PACU automates the discovery of users, roles, resources, and services.
Step‑by‑step guide explaining what this does and how to use it.
1. Understand Your Identity: Run the `whoami` command in PACU. This uses the AWS `GetCallerIdentity` API to confirm the user or role your current keys belong to, along with its associated permissions.
2. Broad Service Enumeration: Use modules like `aws__enum_components` or cloudwatch__enum_logs. PACU will automatically call various AWS APIs (like `DescribeInstances` for EC2 or `ListBuckets` for S3) to map out the account’s resources. This activity maps to MITRE ATT&CK techniques T1580 (Cloud Infrastructure Discovery) and T1087.004 (Cloud Account Discovery).
3. Analyze the Data: All discovered information is stored in PACU’s local SQLite database. Use the `data` command to query enumerated details about specific services, which helps plan your attack path without making excessive, noisy API calls.
3. Hunting for IAM Privilege Escalation Vectors
Privilege escalation is the core goal for an attacker with limited initial access. Misconfigured IAM policies are a primary vector.
Step‑by‑step guide explaining what this does and how to use it.
1. Run a Privilege Escalation Scan: Execute the `iam__privesc_scan` module. This module systematically tests for dozens of known IAM misconfigurations, such as overly permissive `iam:Put` or `iam:PassRole` permissions.
2. Review and Execute Paths: The module presents a list of potential escalation methods. For example, it might find that your user has the `iam:PutUserPolicy` permission, which allows you to attach a new inline policy directly to your own user.
3. Gain Administrator Access: If you select this path, PACU will automatically craft and attach an administrative policy (like AdministratorAccess) to your identity. Confirm the escalation by running `whoami` again, which should now show vastly expanded permissions.
4. Exploiting Publicly Accessible S3 Buckets
Misconfigured storage is a leading cause of cloud data breaches. S3 buckets with overly permissive policies are prime targets.
Step‑by‑step guide explaining what this does and how to use it.
1. Find Buckets: Use PACU’s `s3__enum` module or external tools like `cloud_enum` to discover bucket names.
2. Test for Misconfigurations: Manually test bucket permissions using the AWS CLI. To test for public list permissions, run:
`aws s3 ls s3://[BUCKET-NAME] –no-sign-request`.
If successful, test for public write permissions with:
`aws s3 cp test.txt s3://[BUCKET-NAME]/ –no-sign-request`.
- Exfiltrate or Manipulate Data: If `GetObject` is allowed, download sensitive files. If `PutObject` is allowed, you can upload malicious files (like a webshell) or overwrite critical data, which can be catastrophic if bucket versioning is disabled.
5. Pivoting via EC2 Instances and Snapshots
Compute instances and their associated storage volumes often contain secrets and provide a foothold for further access.
Step‑by‑step guide explaining what this does and how to use it.
1. Enumerate EC2 Instances: Use PACU’s `ec2__enum` module to list all EC2 instances, noting their IDs, states, and associated security groups.
2. Exploit Public AMIs/Snapshots: Attackers can search for publicly shared Amazon Machine Images (AMIs) or EBS snapshots that may contain sensitive data. You can launch an instance from a public AMI or create a volume from a public snapshot, attach it to a controlled instance, and mount it to search for secrets.
3. Extract Secrets from User Data: EC2 instance “user data” is a common location for bootstrapping scripts containing credentials. Use PACU’s `ec2__download_userdata` module to automatically retrieve and inspect this data for secrets.
6. Evading Detection and Disabling Logging
A sophisticated attacker will aim to remain undetected. PACU includes modules to impair cloud defenses and obscure malicious activity.
Step‑by‑step guide explaining what this does and how to use it.
1. Identify Logging Services: Enumerate active AWS security services like CloudTrail, GuardDuty, and VPC Flow Logs using relevant PACU modules.
2. Disable CloudTrail: The `cloudtrail__stop` module can be used to halt logging in a region, creating a blind spot for defenders. The CLI command for this action is:
`aws cloudtrail stop-logging –name [TRAIL-NAME]`.
- Tamper with GuardDuty: To evade the managed threat detection service, an attacker with sufficient permissions could use PACU to list and then disable GuardDuty detectors or allowlist their own IP address.
7. Establishing Persistence in the Cloud Environment
Finally, an attacker seeks to maintain long-term access, even if the initial compromised credentials are discovered and revoked.
Step‑by‑step guide explaining what this does and how to use it.
1. Backdoor IAM Users: Use the `iam__backdoor_users_keys` module to generate new access keys for other IAM users in the account, providing alternative access points.
2. Create Persistent Lambda Functions: Deploy a malicious AWS Lambda function using PACU. You can configure it to be triggered by routine events (like an S3 upload) and have it execute code that opens a reverse shell or exfiltrates new credentials. This maps to MITRE ATT&CK technique T1648 (Serverless Execution).
3. Modify Trust Policies: If you have gained administrative privileges, you could modify the trust policy of an IAM role to allow assumption from an attacker-controlled AWS account, establishing a stealthy backdoor.
What Undercode Say:
- The Attack Surface is Vast and Interconnected: The DEF CON lab demonstrates that cloud attacks are rarely about a single vulnerability. They are “chain reactions” where enumerating a user leads to discovering an over-permissive role, which allows access to a storage bucket containing secrets for a more powerful service account. Each misconfiguration, however minor, can be a critical link in an attack chain.
- The Defender’s Dilemma is Visibility: A key insight from the workshop was highlighting “common blind spots in monitoring services like CloudTrail”. Defenders often lack a unified view of identity, resource, and trust relationships across services like IAM, S3, and EC2. An attacker using PACU automates the creation of this very map to find the path of least resistance, while defenders may struggle to see the same holistic picture.
Prediction:
The sophistication of automated cloud exploitation frameworks like PACU will continue to grow, integrating more AI-assisted discovery of attack paths and complex, multi-account “playbooks.” This will lower the barrier for entry for less skilled attackers, making widespread automated cloud attacks more common. In response, defensive tooling must evolve beyond simple misconfiguration checks. The future lies in Continuous Threat Exposure Management (CTEM) for the cloud, where platforms will need to proactively and continuously simulate attacker behavior—much like the DEF CON lab—to identify and visualize these complex privilege escalation chains before they are exploited. The race will shift from finding single flaws to dynamically modeling and securing entire cloud identity and trust graphs.
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