Application Exhaustion Flood

Application Exhaustion Flood [T1499.003]

Information

• Name: Application Exhaustion Flood

• ID: T1499.003

• Tactics: TA0040

• Technique: T1499

Introduction

Application Exhaustion Flood (T1499.003) is a sub-technique under the MITRE ATT&CK framework categorized within the Impact tactic. It involves overwhelming an application or service with excessive requests or resource-intensive actions to exhaust available resources, resulting in degraded performance or complete denial-of-service (DoS). Attackers leverage this method primarily to disrupt availability and negatively impact operational continuity of targeted systems.

Deep Dive Into Technique

This sub-technique involves attackers sending a high volume of legitimate-looking requests or resource-intensive tasks to an application, causing resource exhaustion and denial-of-service conditions. Unlike volumetric network floods, application exhaustion floods specifically target the application layer (Layer 7 of the OSI model), making them difficult to mitigate using standard network-layer defenses.

Typical execution methods and mechanisms include:

• HTTP/HTTPS Request Flooding:

  • Attackers send numerous HTTP requests that consume significant server resources.

  • Examples include repeated database queries, complex search requests, or resource-intensive page loads.

• Slowloris Attack:

  • Attackers keep HTTP connections open by sending partial requests at regular intervals, quickly consuming available connection pools.

• Resource-Intensive API Calls:

  • Attackers repeatedly invoke APIs that trigger heavy computation or database operations, draining server resources.

• Authentication Exhaustion:

  • Attackers send numerous authentication attempts to consume resources allocated for authentication processes.

Real-world procedures often include:

• Utilizing botnets or distributed attacker-controlled hosts to generate high-volume traffic.

• Exploiting legitimate application features or endpoints that inherently consume considerable resources.

• Crafting requests specifically designed to trigger expensive backend computations or database operations.

When this Technique is Usually Used

Attackers commonly employ Application Exhaustion Flooding in scenarios such as:

• Disrupting Availability:

  • Attackers aim to cause service outages, impacting business continuity or public-facing services.

  • Often used by hacktivists or competitors aiming to damage reputation or financial stability.

• Diversionary Tactics:

  • Attackers use exhaustion floods as distractions to mask other malicious activities, such as unauthorized access or data exfiltration.

• Extortion and Ransom Demands:

  • Criminal groups or threat actors may initiate floods to pressure victims into paying ransoms for restoring service availability.

Attack stages where this technique commonly appears:

• Initial Access:

  • Attackers may use exhaustion floods to disrupt authentication or authorization mechanisms, facilitating unauthorized entry.

• Impact Stage:

  • Primarily employed to directly impact systems and cause operational disruption.

How this Technique is Usually Detected

Detection of Application Exhaustion Floods typically involves monitoring application behavior, resource utilization, and network traffic patterns. Effective detection methods and indicators include:

• Behavioral Monitoring:

  • Sudden spikes in application resource usage (CPU, memory, database queries).

  • Unusual patterns of repeated, resource-intensive requests from individual IP addresses or user agents.

• Traffic Analysis and Anomaly Detection:

  • Tools such as Intrusion Detection Systems (IDS), Web Application Firewalls (WAF), and Security Information and Event Management (SIEM) solutions can identify anomalous request rates or patterns.

  • Detection of Slowloris-type attacks by identifying incomplete or prolonged HTTP sessions.

• Rate Limiting and Threshold Alerts:

  • Setting thresholds for maximum allowed requests per IP or user within specific timeframes.

  • Automatic alerts triggered by exceeding predefined resource utilization thresholds.

Specific Indicators of Compromise (IoCs):

• Unusual number of HTTP status codes indicating server overload (e.g., HTTP 503 Service Unavailable).

• High frequency of incomplete or partial HTTP requests.

• Elevated database or backend server response times correlated with specific endpoints or request patterns.

• Repeated requests originating from suspicious IP addresses or known malicious infrastructure.

Why it is Important to Detect This Technique

Early detection of Application Exhaustion Floods is crucial due to their significant impact on organizational operations and infrastructure availability. Possible impacts include:

• Service Downtime:

  • Prolonged outages can severely impact customer satisfaction, revenue, and organizational reputation.

• Resource Depletion and Performance Degradation:

  • Excessive resource consumption can lead to cascading failures across dependent services or infrastructure components.

• Financial and Operational Costs:

  • Organizations incur costs associated with emergency remediation efforts, infrastructure scaling, and potential regulatory fines.

• Security Posture Weakening:

  • Attackers may leverage exhaustion floods to distract security teams, facilitating other malicious activities such as data breaches or unauthorized access.

Early detection enables organizations to:

• Rapidly initiate mitigation and remediation measures, minimizing downtime and operational disruption.

• Strengthen overall security posture by identifying and addressing vulnerabilities exploited by attackers.

• Reduce financial losses and protect organizational reputation by maintaining service availability and reliability.

Examples

Real-world examples of Application Exhaustion Flood (T1499.003) include:

• Slowloris Attack Against Iranian Government Websites (2009):

  • Attackers utilized the Slowloris tool to maintain multiple incomplete HTTP connections, exhausting available connection pools on targeted Iranian government servers.

  • Resulted in prolonged downtime and reduced availability of government web services.

• Operation Ababil DDoS Attacks on Financial Institutions (2012-2013):

  • Attackers launched sustained application-layer DDoS attacks against major financial institutions, sending resource-intensive HTTPS requests.

  • Attackers employed botnets and custom scripts to flood banking web applications, causing significant disruption to online banking services and customer access.

• Mirai Botnet HTTP Floods (2016 onwards):

  • Mirai malware-infected IoT devices generated massive HTTP floods targeting application-layer resources, overwhelming web servers and causing outages.

  • High-profile targets included online gaming platforms, hosting providers, and DNS providers, resulting in substantial operational disruption and financial losses.

Tools commonly used in Application Exhaustion Flood attacks:

• Slowloris: Tool designed to open multiple slow HTTP connections, exhausting server connection pools.

• LOIC (Low Orbit Ion Cannon): Popular tool among hacktivists to generate high-volume HTTP requests aimed at overwhelming web servers.

• HOIC (High Orbit Ion Cannon): Advanced version of LOIC, capable of generating more complex and resource-intensive HTTP floods.

• Custom scripts and botnets: Attackers frequently leverage custom-developed scripts or commandeer botnets to amplify attack volume and complexity.

Impacts observed from these examples:

• Significant service downtime and customer dissatisfaction.

• Financial losses due to operational disruption and remediation efforts.

• Damage to organizational reputation and trust among customers and stakeholders.