Versatile AI Risk Assessment

AI threat catalogue Attacks on the Running Model and Service Production

Application Denial of Service

Attackers make the AI application unreachable for legitimate users by flooding the application layer with requests or exhausting its resources. The service is heavily slowed or goes down.

As of: October 2026 · Catalogue version 2026.10.24.2 · 5 mitigations · 6 verified sources

Description

This attack targets not the model's computing load but the application layer around it: web server, interface gateway, connections and memory. Attackers flood the service with a mass of requests, often distributed across many hijacked sources (distributed denial-of-service, DDoS), or hold connections open permanently with slowly sent requests (Slowloris) until none remain free. Deliberately exhausting connection and memory reserves also belongs here. It is a classic availability attack on the AI service's operating environment.

Possible impact

The AI service is no longer reachable, or only with delay, for legitimate users, and dependent business processes stall. Beyond the operational outage, there is a risk of penalties under service-level agreements and reputational damage. For high-risk systems, continuous availability is part of the required robustness and operational monitoring.

Example

During a product launch an attacker directs a network of hijacked computers at the customer portal with its AI assistant. The flood of requests overloads the interface gateway, and thousands of genuine visitors receive only error messages.

Recommended mitigations (5)

Compare effects and implementation levels. Expand each entry for the additional classification and rationale.

  • Rate limiting and throttling

    Technical
    Effect
    Preventive, Impact-limiting
    Implementation level
    Application, API & agents, Infrastructure
    Classification and rationale

    Complementary control typeOrganizational & process-based

    Primarily technical: Automated resource controls, budget limits, or runtime boundaries constrain overload, abuse, cost, and cascading failures; complemented by binding workflows.

  • DDoS protection services

    Technical
    Effect
    Preventive, Impact-limiting
    Implementation level
    Application, API & agents, Infrastructure
    Classification and rationale

    Primarily technical: Automated resource controls, budget limits, or runtime boundaries constrain overload, abuse, cost, and cascading failures.

  • Horizontal scaling and autoscaling

    Technical
    Effect
    Preventive
    Implementation level
    Application, API & agents, Infrastructure
    Classification and rationale

    Primarily technical: Automated resource controls, budget limits, or runtime boundaries constrain overload, abuse, cost, and cascading failures.

  • Circuit breakers and timeouts

    Technical
    Effect
    Preventive, Impact-limiting
    Implementation level
    Application, API & agents, Infrastructure
    Classification and rationale

    Primarily technical: Automated resource controls, budget limits, or runtime boundaries constrain overload, abuse, cost, and cascading failures.

  • Capacity planning

    Organizational & process-based
    Effect
    Preventive
    Implementation level
    Infrastructure, Organization, Use & operations
    Classification and rationale

    Complementary control typeTechnical

    Primarily organizational and process-based: Defined selection, operating, or lifecycle procedures make the control binding and repeatable; complemented by technical implementation.

Framework mappings

Verified locations in OWASP, NIST AI RMF, MITRE ATLAS, the EU AI Act and further frameworks. The mappings are taxonomic, not evidence of compliance.

MITRE ATLAS AML.T0029EU AI Act Article 26(5) · Article 55(1)(d) · Article 9(1), 9(2)(a), 9(2)(d)BIML BIML-LLM inference:9 · BIML78 system:10

Verified references (6)

Every reference states the framework, the exact location and the publishing organisation.

EU AI Act obligations related to this threat

The obligations from the obligations compass whose articles the catalogue maps to this threat. Each leads to its entry with core, action step and evidence; whether it applies to you depends on role and risk class.

  • Establish and operate a risk management system Art. 9 · applies from Annex III: 2 December 2027 · Annex I: 2 August 2028

    Statutory roles: Provider, Product manufacturer. Classes: High-risk under Annex III, High-risk as a product or safety component.

    This reference is a review prompt. A threat match alone does not establish applicability.

  • Monitor operation and suspend on risk Art. 26 Abs. 5 · applies from Annex III: 2 December 2027 · Annex I: 2 August 2028

    Statutory roles: Deployer. Classes: High-risk under Annex III, High-risk as a product or safety component.

    This reference is a review prompt. A threat match alone does not establish applicability.

  • Evaluate and mitigate systemic risks Art. 55 · applies from 2 August 2025

    Statutory roles: Provider of a general-purpose AI model. Classes: Model with systemic risk.

    This reference is a review prompt. A threat match alone does not establish applicability.

All 62 obligations by role, risk class and deadline in the obligations compass

More entries from the topic group Attacks on the Running Model and Service.

Model Theft Attackers create a working copy of a proprietary AI model, either by querying it at scale or by breaking into the infrastructure. Adversarial Inputs Attackers alter an input in a way that is minimal and imperceptible to humans, so that the AI model classifies it incorrectly. Model Denial of Service Attackers overload the AI model with especially expensive requests until the service slows down or fails.

Matching use cases

This list shows where to review this threat, rather than how high the risk is.

Particularly important for:

Typical for:

For 42 further use cases, relevance depends on the system design, for example whether it accepts queries directly through an interface or is accessible over a network. Show these use cases

Frequently asked questions

What is Application Denial of Service?
Attackers make the AI application unreachable for legitimate users by flooding the application layer with requests or exhausting its resources. The service is heavily slowed or goes down.
Which mitigations help against Application Denial of Service?
The catalogue lists 5 mitigations, each with control type, effect and implementation level. First among them are Rate limiting and throttling, DDoS protection services and Horizontal scaling and autoscaling.
Which EU AI Act obligations does Application Denial of Service touch?
The catalogue maps this threat to Art. 9, Art. 26 Abs. 5 and Art. 55 of the EU AI Act. In the obligations compass this leads to: Establish and operate a risk management system, Monitor operation and suspend on risk and Evaluate and mitigate systemic risks. Whether an obligation applies depends on role, risk class and deadline.

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Cite this entry

For reports, policies or internal documents; the link leads directly to this entry.

“Application Denial of Service”. Versatile AI Risk Assessment, AI threat catalogue, as of October 2026.
https://www.versatile-ai-risk-assessment.com/en/wissensbasis/threats/application-denial-of-service/

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