AI RED TEAMING & MODEL SECURITY

Secure Your LLMs. Prevent AI Breaches.

AI systems introduce unique vulnerabilities like data poisoning, prompt injection, and opaque model decisions. Don't risk the rising global average breach cost of $4.88 million.

AI Red Teaming

Adversarial testing against prompt injection & jailbreaks.

Model Integrity

Prevent data poisoning & supply chain attacks.

Compliance

Align with NIST AI RMF, EU AI Act, and OWASP LLM Top 10.

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Traditional Testing Fails:
The AI Attack Surface is Exploding

Standard security tools aren't built for probabilistic systems. AI introduces novel attack vectors that bypass traditional firewalls and scanners.

Novel Attack Vectors

Prompt Injection & Adversarial Inputs: Attackers craft inputs to subvert LLM instructions, extract internal data, or elicit prohibited output.

Critical for APIs & LLMs

Data Integrity Risks

Data Poisoning & Backdoors: Malicious data injected into training sets can manipulate model behavior, creating hidden triggers.

Critical for Data Pipelines

The Human Element

Evolving Social Engineering: GenAI has turbo-charged phishing (1,200%+ increase). Automated scanners cannot simulate these creative attacks.

Critical for Resilience

AI Red Teaming:
Adversarial Testing for GenAI

We go beyond standard pentesting to simulate adversarial attacks specifically targeting Large Language Models (LLMs) and ML pipelines.

AI (Machine Intelligence)

Provides breadth, speed, and continuous coverage. Excels at scanning thousands of endpoints and predicting defect hotspots. Reduces test planning from days to hours.

Human (Expert Intelligence)

Provides depth, strategy, and context. Skilled ethical hackers think like attackers, chain vulnerabilities, and prioritize findings by business impact.

Security Coverage Comparison

Traditional PentestingLimited Scope
Automated ScanningHigh Volume, Low Context
Hybrid AI PentestingComplete Coverage

99.8%

Detection Rate

78%

Faster Remediation

24/7

Continuous Monitoring

Comprehensive AI Security Evaluation

Aligned with industry-recognized frameworks like PTES and OWASP.

Model Evaluation & Robustness

Assess resilience to adversarial inputs, prompt injection/jailbreak attempts, and risk of model inversion.

Data Pipeline Security

Simulate data poisoning attacks against training data and verify data provenance and supply chain integrity.

API and Interface Testing

Fuzzing inputs, identifying prompt injection flaws in conversational interfaces, and testing rate limits.

Infrastructure & Cloud Security

Examine GPU access, encryption of model artifacts, and credential hygiene in CI/CD pipelines.

Human Element Simulation

Conduct ethical social engineering campaigns mirroring modern generative AI-enhanced phishing tactics.

Governance & Compliance

Validate human oversight mechanisms and alignment with frameworks like NIST AI RMF and EU AI Act.

For Executives & C-Suite

ROI and Cost Avoidance: Proactive testing costs a fraction of the average $9.48 million breach cost.

  • Ensure compliance with DORA & EU AI Act
  • Protect brand reputation and customer trust
  • measurable risk reduction

For Technical Leads

Methodology & Specificity: Adherence to PTES methodology with deep dives and clear remediation guidance.

  • Integrates with CI/CD pipelines
  • Validates model integrity & provenance
  • Comprehensive API & microservices testing

Ready to Transform Security Anxiety into Measurable Resilience?

Get a personalized AI penetration testing program tailored to your specific models and infrastructure.

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