⚙️ AWS STS: Hidden Privilege Escalation

#cybersecurity #security #programming #devops

Abstract

This article dissects the often-misunderstood security implications of AWS Security Token Service (STS) and temporary credentials. While STS is essential for least-privilege cloud architectures, its complexity introduces significant avenues for lateral movement and privilege escalation. We explore how misconfigurations in AssumeRole policies and inadequate monitoring create persistent backdoors, offering technical analysis and mandatory defense strategies for security professionals.

High-Retention Hook

I learned the hard way that a 15-minute temporary session token can cause permanent damage. During a recent client engagement focused on CI/CD pipeline security, we compromised a non-production service running in Fargate. The resulting AWS temporary key was set to expire quickly, and the DevSecOps team felt safe. However, that token allowed us to immediately execute a high-privilege sts:AssumeRole command, granting us access to the cross-account staging environment. The initial ephemeral token was irrelevant; the resulting session, created through a weak trust policy, became our persistent beachhead. We weren't exploiting a flaw in STS, but a failure to fully grasp how delegated trust propagates risk.

Research Context

The modern cloud environment rejects long-lived access keys. Best practices, often aligned with NIST guidance (e.g., NIST SP 800-204A), mandate the use of temporary credentials generated via AWS STS, specifically through the AssumeRole, GetFederationToken, or GetSessionToken API calls. This paradigm shift improves security hygiene by limiting exposure time.

However, complexity is the enemy of security. For Security Operations Center (SOC) analysts and Threat Hunters, tracking the origin, use, and termination of these temporary identities is exponentially harder than monitoring static IAM users. The MITRE ATT&CK framework recognizes this risk under T1098.006 (Account Access via Identity Provider) and T1537 (Transfer Data to Cloud Account), acknowledging that establishing trust relationships is a key target for sophisticated adversaries.

Problem Statement

The fundamental security gap lies in the Trust Policy of the assumed role. Many organizations focus heavily on the Permissions Policy (what the role can do) but overlook the critical details of the Trust Policy (who can assume the role and under what conditions).

A common misconfiguration we encounter is overly permissive Service Control Policies (SCPs) combined with Trust Policies that are too broad regarding Principal and ExternalId. For instance, roles trusted by specific AWS accounts are often written simply as:

"Principal": { "AWS": "arn:aws:iam::123456789012:root" }

This assumes the entire account is trustworthy. If a low-privilege service in the source account is compromised, the attacker inherits the capability to assume the high-privilege role in the target account, achieving immediate lateral movement and privilege escalation. The temporary nature of the credential provides zero defense against this immediate attack vector.

Methodology or Investigation Process

To audit this risk, our methodology involves a three-step process focusing on policy analysis and log review:

Policy Enumeration: We use tools like CloudSploit or custom Python scripts based on boto3 to enumerate all IAM Roles, focusing specifically on their Trust Policies. We prioritize roles where the Action is sts:AssumeRole and examine the Condition block.
Weak Trust Identification: We flag any Trust Policy lacking strong conditional keys, such as aws:SourceVpce, sts:ExternalId, or sts:SourceIdentity. Specifically, roles trusting the root ARN of an entire account or using the sts:SourceIp condition vaguely are immediately prioritized for investigation.
CloudTrail Analysis: We pivot to CloudTrail logs, filtering for high-volume AssumeRole events. We look for discrepancies between the userName (the entity making the request) and the sessionName (the identifier provided by the entity). An attacker often uses a suspicious or non-standard session name, making this field a critical hunting indicator.

Findings and Technical Analysis

The technical pathway for escalation is straightforward once a weak Trust Policy is identified. Consider a scenario where an attacker compromises a serverless function (e.g., Lambda) with basic S3 read access. If that Lambda’s execution role is allowed to assume a higher-privileged administrative role in a different account due to a weak Trust Policy, the attacker can leverage the compromised session credentials.

Credential Acquisition: The attacker extracts the ephemeral keys (Access Key ID, Secret Access Key, Session Token) from the compromised Lambda environment variables.
Role Assumption: They execute the aws sts assume-role command, specifying the ARN of the high-privilege role in the target account. Crucially, they may also pass a new, custom SessionName.
Persistence: The resulting temporary credentials grant the attacker the high-privilege capabilities defined by the target role’s Permission Policy, potentially enabling actions like creating new permanent IAM users, modifying logging configurations, or initiating data exfiltration. The short TTL of the original Lambda token is entirely irrelevant at this stage, as the attacker is operating with a brand new, powerful token.

This mirrors elements of the 2019 Capital One breach, where a former employee leveraged a misconfigured Web Application Firewall (WAF) running on an EC2 instance to gain access to the underlying instance role metadata. Although the root cause was different (SSRF vs. IAM policy), the concept of using a low-privilege compute resource to steal and leverage underlying credentials for massive impact remains a core cloud threat model.

Risk and Impact Assessment

The risk associated with STS misconfiguration is a failure of isolation. A compromise that should be contained to a single microservice or non-critical environment can instantly breach the security boundary of a production environment or a central security account.

Impacts include:

Data Exfiltration: Access to sensitive data stores (S3, RDS).
Infrastructure Destruction: Ability to delete core networking components (VPCs, security groups).
Backdoor Creation: Establishment of new, permanent access keys or SAML federation points, allowing the attacker long-term persistence even after the initial temporary tokens expire.

The difficulty in tracking these temporary sessions means that standard anomaly detection often fails. If the attacker operates within the legitimate permissions of the assumed role, the activity may appear benign to superficial monitoring, leading to delayed detection (Dwell Time).

Mitigation and Defensive Strategies

Defending against STS abuse requires shifting security focus from "what" the role can do to "who/where/how" the role can be assumed.

Enforce Strong Conditional Keys: When defining Trust Policies for cross-account roles, never trust an entire account ARN. Always use granular conditions, especially sts:ExternalId (a shared secret) and aws:SourceArn (to restrict the assumption request to a specific resource, like a single Lambda function or specific EC2 instance profile).
Implement Least-Privilege Session Policies: Use AssumeRole parameters to inject a granular inline policy (a Session Policy) that further restricts the resulting session token’s permissions, regardless of the role’s primary Permission Policy. This acts as a security brake.
Strictly Audit CloudTrail AssumeRole: Implement specific alerts for AssumeRole events originating from external IP addresses or from internal principals that do not typically request such access (e.g., a Lambda function suddenly assuming an Admin role). Monitor the sessionName parameter for unexpected or malicious strings.
Use Identity Providers for Human Access: Where possible, leverage AWS IAM Identity Center (SSO) or external IdPs (Okta, Azure AD) rather than custom AssumeRole scripts for human administrators, centralizing authentication control.

Researcher Reflection

When I started diving into vulnerability research, the focus was always on finding the buffer overflow or the classic SQL injection. But in the cloud, the real exploits are logical failures of identity and trust. The sheer cognitive load required to correctly manage complex IAM policies and session constraints is the single biggest security challenge today. Honestly, reading AWS documentation on policy evaluation order sometimes feels like deciphering ancient hieroglyphs. We need better visualization and analysis tools to model these trust relationships before they become operational failures.

Conclusion

AWS STS is not inherently vulnerable, but its operational complexity introduces severe privilege escalation risks when Trust Policies are overly permissive. Security researchers and practitioners must move beyond simple key rotation and focus intensely on auditing the logical flow of identity delegation and conditional policy enforcement. Temporary credentials grant access, but trust policies grant permanence.

Discussion Question

Given the complexity of cross-account access and conditional keys, what operational control (beyond CloudTrail) have you found most effective for immediately detecting unauthorized or anomalous AssumeRole usage within a high-volume microservices environment?

Written by - Harsh Kanojia

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