Tell me about AI Red Teaming
AI Red Teaming is the practice of proactively testing AI systems to identify vulnerabilities before malicious actors can exploit them. Think of it as "ethical hacking" for AI models—our team simulates real-world attacks to uncover weaknesses in your AI infrastructure, ML models, and AI-powered applications.
1. Prompt Injection
Manipulating LLM inputs to alter behavior or extract sensitive data
2. Insecure Output Handling
Failing to sanitize LLM outputs before downstream processing
3. Training Data Poisoning
Malicious data manipulation during model training phases
4. Model Denial of Service
Overwhelming LLMs with resource-intensive inputs
5. Supply Chain Vulnerabilities
Compromised third-party components or pre-trained models
6. Sensitive Information Disclosure
Unintended exposure of confidential data in responses
7. Insecure Plugin Design
LLM plugins with excessive permissions or poor validation
8. Excessive Agency
Granting AI systems too much autonomy without oversight
9. Overreliance
Blindly trusting LLM outputs without human verification
10. Model Theft
Unauthorized extraction or replication of proprietary models
🎯 Adversarial Attacks
Crafting inputs that cause model misbehavior
💉 Prompt Injection
Injecting malicious instructions via user input
🗄️ Data Poisoning
Compromising training data integrity
📤 Model Extraction
Stealing model architecture or weights
🔍 Inference Attacks
Extracting training data through queries
🚪 Backdoor Attacks
Hidden triggers for malicious behavior
🔓 Jailbreaking
Bypassing safety guardrails
📡 API Exploitation
Attacking AI service endpoints
Adversarial Attack Testing
Prompt injection, data poisoning, model extraction, evasion techniques
AI Defense Assessment
Security control audits, monitoring gaps analysis, incident response testing
Model Robustness Testing
Edge case testing, input validation, failure mode analysis
Training Data Security
Pipeline security, data leakage detection, integrity verification
API & Integration Security
Endpoint testing, authentication, rate limiting vulnerabilities
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