Steal Application Access Token
Steal Application Access Token [T1528]
Information
Name: Steal Application Access Token
ID: T1528
Tactics: TA0006
Introduction
Steal Application Access Token (Technique ID: T1528) is a credential access technique defined within the MITRE ATT&CK framework. Attackers use this method to obtain application-level access tokens that provide authentication and authorization privileges within cloud environments or software applications. By stealing these tokens, adversaries can bypass standard authentication mechanisms, allowing unauthorized access to sensitive data, resources, or services. This technique is particularly relevant in cloud-based and hybrid environments where tokens are commonly used for authentication and authorization.
Deep Dive Into Technique
Application access tokens are typically short-lived, cryptographically signed tokens (such as OAuth tokens, JWT tokens, or similar) that applications use to authenticate themselves and access specific resources or APIs. Attackers target these tokens because they provide immediate and often extensive access without requiring additional credentials.
Attackers may use several methods to steal application access tokens, including:
Intercepting Network Traffic:
Capturing tokens transmitted unencrypted over insecure channels.
Conducting man-in-the-middle (MITM) attacks to intercept tokens during transit.
Exploiting Vulnerabilities in Applications or APIs:
Leveraging application vulnerabilities such as injection attacks, insecure direct object references, or broken authentication mechanisms.
Exploiting API misconfigurations or improper token handling.
Accessing Unsecured Storage Locations:
Retrieving tokens stored insecurely in plaintext files, environment variables, or configuration files.
Extracting tokens from logs or debugging outputs mistakenly left enabled in production environments.
Social Engineering and Phishing:
Tricking developers or administrators into revealing tokens through phishing attacks.
Leveraging compromised developer accounts or endpoints to extract tokens.
After obtaining tokens, attackers typically use them to:
Access cloud resources, databases, or APIs.
Elevate privileges within applications or cloud services.
Pivot laterally within the network or cloud infrastructure.
Exfiltrate sensitive data or disrupt services.
When this Technique is Usually Used
Attackers commonly employ the technique of stealing application access tokens in various attack scenarios and stages, including:
Initial Access and Reconnaissance:
Capturing tokens during initial compromise to gain a foothold within cloud environments or application infrastructure.
Privilege Escalation:
Leveraging stolen tokens to escalate privileges and move vertically within cloud or application infrastructure.
Lateral Movement:
Using tokens to pivot laterally between different applications, APIs, or cloud resources.
Persistence:
Continuously refreshing or renewing tokens to maintain persistent access without detection.
Data Exfiltration:
Utilizing stolen tokens to access sensitive data, databases, or storage services to exfiltrate critical information.
Impact and Disruption:
Employing tokens to disable security controls, delete data, or disrupt services.
How this Technique is Usually Detected
Detection of stolen application access tokens involves monitoring, logging, and analyzing various indicators and behaviors, including:
Monitoring Token Usage Patterns:
Identify unusual or unexpected token usage patterns, such as tokens being used from unfamiliar IP addresses, geographic locations, or devices.
Detect tokens being used outside of normal business hours or typical usage patterns.
Analyzing Logs and Audit Trails:
Regularly audit application and API logs to identify unauthorized or anomalous token access attempts.
Monitor cloud provider logs (e.g., AWS CloudTrail, Azure Monitor, Google Cloud Audit Logs) for suspicious token activities.
Implementing and Monitoring Security Tools:
Use Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS) to detect anomalous traffic or token exfiltration attempts.
Deploy Security Information and Event Management (SIEM) solutions to correlate log data and identify suspicious token usage.
Behavioral Analysis and Anomaly Detection:
Utilize User and Entity Behavior Analytics (UEBA) solutions to detect abnormal token usage patterns indicative of compromised tokens.
Employ machine learning and AI-driven analytics to identify deviations from typical token usage behavior.
Indicators of Compromise (IoCs):
Repeated token usage from multiple distinct geographic locations or IP addresses.
Tokens being used to access resources or APIs outside their usual scope or permissions.
Unexpected spikes in token-related API requests or access attempts.
Tokens being used after their expected expiration or revocation.
Why it is Important to Detect This Technique
Early detection of stolen application access tokens is critical due to the significant potential impacts on systems, networks, and overall organizational security. Possible impacts include:
Unauthorized Access and Data Breaches:
Attackers can use stolen tokens to access sensitive data, intellectual property, or personal information, leading to data breaches and regulatory violations.
Privilege Escalation and Lateral Movement:
Compromised tokens may allow attackers to escalate privileges, gain administrative access, and move laterally across cloud or application infrastructures.
Operational Disruption and Service Downtime:
Attackers may disrupt services, delete critical data, or disable security mechanisms, causing significant operational downtime and financial losses.
Reputation Damage and Compliance Violations:
Breaches resulting from stolen tokens can lead to loss of customer trust, reputational damage, regulatory fines, and legal consequences.
Persistent and Stealthy Compromise:
Stolen tokens can enable attackers to maintain persistent, stealthy access, making detection and remediation more challenging.
Early detection and remediation minimize these impacts by:
Quickly revoking compromised tokens and limiting attacker access.
Preventing further lateral movement and escalation within the environment.
Reducing the risk of data exfiltration, operational disruption, and reputational harm.
Examples
Real-world examples showcasing the use of stolen application access tokens include:
Capital One Data Breach (2019):
Attack Scenario: Attacker exploited a misconfigured web application firewall (WAF) and used stolen AWS IAM role credentials (tokens) to access sensitive data stored in Amazon S3 buckets.
Tools Used: AWS CLI, custom scripts.
Impact: Exposure of over 100 million customer records, including personal information, credit scores, and financial data. Capital One faced significant regulatory fines, lawsuits, and reputational damage.
Uber Data Breach (2016):
Attack Scenario: Attackers accessed a private GitHub repository containing AWS access tokens. They subsequently used these tokens to access AWS S3 buckets containing sensitive data.
Tools Used: GitHub, AWS CLI.
Impact: Exposure of personal information of approximately 57 million customers and drivers. Uber paid a ransom to attackers and faced regulatory fines, legal actions, and significant reputational harm.
Imperva Data Breach (2019):
Attack Scenario: Attackers compromised an AWS API key (token) stored insecurely, allowing unauthorized access to cloud databases containing customer data.
Tools Used: AWS CLI, standard HTTP clients.
Impact: Exposure of sensitive customer data, including email addresses, hashed passwords, and API keys. Imperva faced regulatory scrutiny, customer notifications, and reputational damage.
Codecov Supply Chain Attack (2021):
Attack Scenario: Attackers modified Codecov's Bash Uploader script to exfiltrate environment variables, including application access tokens, from thousands of customer CI/CD pipelines.
Tools Used: Modified Bash scripts, HTTP exfiltration methods.
Impact: Attackers gained unauthorized access to multiple organizations' sensitive repositories, source code, and infrastructure, leading to widespread security investigations, remediation efforts, and reputational harm.
These examples illustrate the severity and wide-ranging impacts of stolen application access tokens, highlighting the critical need for robust detection, monitoring, and preventive security measures.
Last updated
Was this helpful?