Attack Coverage
Check Point AI Red Teaming evaluates your GenAI applications across a comprehensive set of adversarial techniques organized into attack categories. Our attack library is continuously updated based on real-world threat intelligence.
Attack Categories
Red organizes attacks into three main categories. A basic scan in the dashboard includes Security, Safety, and Responsible categories (23 objectives total). Attack strategies include, but are not limited to, Prompt Injection, Jailbreaks, Multi-lingual, Multi-turn, and Indirect techniques. Indirect attacks reach the agent through content it loads rather than through a user message. Red’s first indirect strategy, Tool Response Poisoning, delivers payloads through tool results.
Default Objectives
A basic scan covers 23 objectives: 4 Security, 8 Safety, and 11 Responsible. Security
covers ways an application can be compromised; Safety covers harmful content; and
Responsible covers legal, reputational, or ethical failures. Pass an objective ID in
objectives when creating a scan.
How Attacks Work
Attack Generation
For each objective, Red generates targeted attack probes based on:
- The attack objective’s goal and expected harmful output
- The target’s profile (summary, allowed/forbidden actions)
Risk Score Calculation
Your overall risk score is the percentage of attacks that succeeded:
Customizing Attack Scope
Basic Scan in the Dashboard
If you start a basic scan in the dashboard without choosing objectives, Red covers all
23 default objectives. SDK scans require at least one objective
ID (built-in or saved custom) or a custom objective definition in the scan request,
except for smoke, which uses fixed probes. To scan all 23 defaults through the SDK,
pass their IDs explicitly.
Custom Scope
You can customize your scan scope in two ways:
Scan plan (dashboard): select or deselect specific objectives under Test Coverage before starting a scan.
Custom objectives: test risks specific to your application by defining your own goal and success criteria, in the Test Objectives library or directly in an SDK scan request. See Custom Objectives.
Continuous Updates
Our attack library evolves continuously based on:
- Proprietary threat intelligence from 100K+ daily Gandalf attacks
- Check Point’s dedicated AI security research team
- Academic research and industry publications
- Real-world attack patterns observed across our Red team engineers
Learn More
- Understand foundation model vulnerabilities with the AI Model Risk Index
- Read our AI Red Teaming Guide
- Explore the LLM Security Playbook