The AI Blind Spot
Your security controls are passing. Your AI systems may still be exposed.
The AI Blind Spot whitepaper reveals how attackers manipulate trusted prompts, data, and workflows without triggering the warnings traditional security tools rely on.
Download the whitepaper to learn:
- Why passing security checks can create false confidence
- How Indirect Prompt Injection and RAG Pipeline Hijacking exploit legitimate system behavior
- Where traditional controls may miss AI-specific attack paths
- Why testing from an attacker's perspective is critical to validating AI resilience
What Demonstrated Readiness Looks Like
AI attacks can exploit legitimate system behavior without triggering traditional security controls. Organizations cannot rely on automated checks or completed training to show that their teams are prepared to find those attacks.
Demonstrating cyber readiness helps organizations:
- Verify that practitioners can identify AI-specific attack paths
- Reveal skills gaps before teams are responsible for securing AI systems
- Determine who can test AI systems under realistic conditions
- Give leaders evidence to support oversight and workforce decisions
How OffSec Helps
OffSec helps organizations build security teams that can test beyond automated checks and evaluate AI systems from an attacker's perspective.
Through hands-on, proof-based learning, practitioners work through realistic scenarios where they must:
- Recognize attacks hidden within legitimate system behavior
- Trace AI-specific attack paths across connected systems
- Evaluate whether security controls hold under attack
- Identify and document weaknesses and their potential impact
Organizations gain stronger evidence of how their teams can assess AI resilience in practice.
AI Red Team Upskilling
Organizations need to show that their practitioners can progress from their current skill level to testing AI systems under realistic conditions. The AI Red Teaming Upskill Program makes that progress measurable by assessing baseline skills, tailoring each practitioner's path, and validating their development toward the advanced AI Red Team Operator role.
Why Organizations Choose OffSec
Train in Realistic AI Environments
Hands-on labs reflect how AI models, applications, data pipelines, agents, and infrastructure operate together.
Practice AI-Specific Attacks
Practitioners carry out the techniques used to manipulate modern AI systems and observe their impact.
Assess the Full AI Attack Surface
Training extends beyond model behavior to the applications, data, integrations, and infrastructure that support AI systems.
Develop Technical Judgment
Realistic scenarios require practitioners to investigate unexpected behavior, connect weaknesses, and adapt their approach as an attack develops.
Build Evidence of AI Readiness
OffSec helps organizations establish current capability, develop the skills they are missing, and prove that those skills can be applied.
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Foundation
Establish What Your Team Can Do
Assess existing knowledge and identify where practitioners need further development.
Advanced
Test Skills in Realistic Environments
Build hands-on experience attacking AI applications, agents, pipelines, and infrastructure through AI-300 and the AI Red Teaming Upskill Program.
Enterprise scale
Prove Capability in Practice
Build hands-on experience attacking AI applications, agents, pipelines, and infrastructure through AI-300 and the AI Red Teaming Upskill Program.
