Hijacking the Cloud: An AWS Takeover and RCE Tale

In today’s fast-paced cloud era, even seasoned engineers can overlook subtle misconfigurations that pave the way for catastrophic breaches. This deep-dive explores a hypothetical—but entirely plausible—attack chain within an AWS environment. Through a blend of Server-Side Request Forgery (SSRF), AWS metadata abuse, and Remote Code Execution (RCE), an attacker achieves full cloud account compromise. We’ll also cover how defenders could have prevented each stage of the attack.

Cloud Stack Overview

The scenario involves a typical AWS-based architecture common among modern startups and enterprises:

• Public API Gateway routing to Lambda functions for image processing

• Amazon S3 hosting static assets like images, CSS, and JS

• Amazon ECS clusters running containerized microservices (Node.js, Python)

• Amazon RDS (MySQL) for transactional data, accessible only via a bastion EC2 instance restricted to corporate IPs

• IAM with scoped roles, but a few overly permissive policies

  
  

Despite following many AWS best practices—like separation of environments, least privilege, and CloudTrail logging—a single SSRF vulnerability led to a complete compromise.

Phase 1: Entry via SSRF and Metadata Abuse

Reconnaissance and Bug Discovery

An attacker begins probing the environment and discovers an API endpoint:

GET /api/v1/images?url=<external_url>

This endpoint is used to fetch and process external images. However, it's vulnerable to Server-Side Request Forgery (SSRF).

Exploiting SSRF to Access IMDS

By supplying a crafted request like:

/api/v1/images?url=http://169.254.169.254/latest/meta-data/iam/security-credentials/

…the attacker tricks the server into querying the Instance Metadata Service (IMDS), revealing the IAM role name attached to the Lambda runtime.

Tech Spotlight

• IMDS (Instance Metadata Service): Exposes metadata and credentials for the instance or runtime environment.

• SSRF: Exploits server behavior to make internal HTTP requests on behalf of the attacker.

  
  

Phase 2: Credential Harvesting and Privilege Escalation

Retrieving Temporary Credentials

Next, the attacker uses the exposed role name to query:

http://169.254.169.254/latest/meta-data/iam/security-credentials/<RoleName>

They now have temporary AWS credentials (AccessKeyId, SecretAccessKey, SessionToken).

Enumerating and Exploiting IAM Permissions

With these credentials, the attacker discovers that the Lambda role has:

• iam:ListUsers

• sts:AssumeRole on another role in a different AWS account

By chaining sts:AssumeRole into a more privileged role, they escalate access—eventually gaining admin permissions.

Tech Spotlight

• STS AssumeRole: Allows an entity to assume another IAM role, enabling cross-account access and privilege escalation.

• IAM Policy Misconfiguration: Even one Resource: "*" can grant excessive access.

Phase 3: Spinning Up Malicious Infrastructure

With admin-level credentials, the attacker now has full control. They can:

• Launch a backdoor EC2 in a quiet VPC, assign it a powerful IAM role, and control it remotely

• Inject malicious Lambda functions that manipulate environment variables or call the AWS SDK to tamper with other services

• Persist access by:

  • Modifying Service Control Policies (SCPs) to trust attacker accounts

  • Setting up CloudWatch triggers that reinvoke rogue Lambda functions on specific events

    
    

Phase 4: Remote Code Execution (RCE) and Internal Lateral Movement

Lambda RCE via Code Injection

Using AWS APIs, the attacker modifies existing Lambda functions with:

• UpdateFunctionCode to inject backdoors

• Environment variable patching to leak secrets on invocation

ECS Container Compromise

By editing ECS service definitions, they:

• Add a sidecar container with a reverse shell

• Leverage the task role to interact with other services (like S3 or RDS)

Pivot to RDS via Bastion

With ECS networking allowing outbound traffic to the bastion host, the attacker pivots and extracts:

• Full RDS database dumps containing sensitive PII and payment data

Impact of the Compromise

• Data Exfiltration: Theft of customer records, payment tokens, credentials

• Service Disruption: Malicious CloudFormation stacks used to delete or disrupt resources

• Compliance Violations: Breaches of GDPR, CCPA, or PCI-DSS

• Financial Damage: Downtime, incident response, legal costs, regulatory fines

  
  

Lessons Learned & Mitigation Strategies

1. Enforce IMDSv2

• Require session-based tokens to access metadata.

• Disable IMDSv1 entirely where possible.

2. Tighten IAM Policies

• Avoid Resource: "*" in all but strictly controlled cases.

• Use permission boundaries and session policies to constrain assumed roles.

3. Harden Public APIs

• Sanitize inputs rigorously.

• Whitelist allowable domains or use a fetch proxy to inspect external calls.

4. Segment and Isolate Networks

• Place sensitive workloads (like databases) in private subnets.

• Block egress to 169.254.169.254 wherever possible (via NAT or host-level firewalls).

5. Continuous Monitoring & Alerting

• Enable GuardDuty to detect anomalous activities (e.g., STS abuse).

• Set up alerts for:

  • New role creation

  • Unexpected Lambda updates

  • Suspicious CloudFormation activity

    
    

Conclusion

Cloud platforms like AWS deliver immense agility—but with that power comes the need for relentless security diligence. This scenario demonstrates how a small SSRF vulnerability in a Lambda function can lead to a full-scale AWS account takeover.

By enforcing IMDSv2, adhering to least privilege, monitoring cloud activity, and practicing defence-in-depth, teams can significantly reduce their risk of catastrophic cloud breaches.

Stay proactive. Stay secure.