Cybersecurity for the AI Era
Security that assumes someone is already inside.
What is Cybersecurity for the AI Era?
The perimeter stopped being the control years ago. Your people are remote, your systems are someone else's cloud, and now you have AI agents holding credentials and making requests at three in the morning. The question isn't how to keep attackers out. It's what they can reach once they're in.
So most of this work is identity. Who is this, what are they allowed to touch, and how would we know if that changed. That covers Zero Trust architecture, IAM and access reviews, machine and service identity, and, increasingly the awkward one, identity for AI agents, which need credentials but can't do MFA and don't get fired when they misbehave.
We won't sell you a tool to fix this. Most breaches we see aren't a missing product; they're an account that should have been removed in 2023, or a service principal with permissions nobody ever scoped. That's boring to fix and it's usually the fix.
Services provided
What the data says
Prompt injection is now the #1 vulnerability in AI applications, present in over 90% of deployed LLM-based systems that haven’t been specifically hardened against it. (Source: OWASP Top 10 for LLM Applications 2025)
AI-powered threat detection identifies breaches an average of 68 days faster than traditional rule-based systems, reducing breach costs by $1.8M on average. (Source: IBM Cost of a Data Breach Report 2025)
NIST finalized post-quantum cryptography standards in 2024. Organizations with 10+ year data retention requirements should begin PQC migration planning now. (Source: NIST PQC Standardization Project)
Global cybersecurity spending is projected to exceed $300 billion in 2026, with AI security and AI-powered defense as the two fastest-growing sub-segments. (Source: Cybersecurity Ventures Annual Report)
61% of organizations deploying AI have no formal process for assessing AI-specific security risks, they apply traditional AppSec testing that misses AI-unique vulnerabilities. (Source: Gartner AI Security Survey)
Where Ganexa stands out
We start with identity, not products. It's where the actual risk is, and it's the least exciting slide in the deck.
We'll tell you when the fix is unglamorous. Deleting stale accounts beats buying a platform, and we'd rather say so.
AI agents get treated as identities. They hold credentials and act on their own; most access models have no idea what to do with that.
Security that survives us leaving. If a control needs a specialist to operate, it stops working the month we go.
Your engagement roadmap
Threat Assessment
Week 1–2Inventory all AI systems and their attack surfaces. Assess current security posture against OWASP Top 10 for LLMs. Identify crypto assets vulnerable to quantum threats. Map gaps against NIST AI RMF.
AI Security Threat Assessment report with risk-ranked vulnerabilities
Architecture & Policy
Week 3–4Design Secure AI Development Lifecycle (SecAI) framework. Build AI security policies and incident response procedures. Design post-quantum crypto migration roadmap. Recommend AI-powered defense tool enhancements.
SecAI Framework, AI security policies, and PQC migration plan
Red-Team & Harden
Week 5–8Execute adversarial red-teaming against high-risk AI systems: prompt injection, data poisoning, model extraction, jailbreaking. Harden systems based on findings. Implement AI-powered threat detection enhancements.
Red-team findings report, hardened AI systems, and enhanced threat detection
Monitor & Sustain
Week 9–12Deploy continuous AI security monitoring. Train security team on AI-specific threats and response. Establish ongoing red-team cadence. Begin PQC pilot implementation for highest-priority systems.
Continuous monitoring system, trained team, red-team schedule, PQC pilot
Built for where you are
Company deploying customer-facing AI
“We’re launching an AI chatbot for customer service but our security team doesn’t know how to test it. Traditional penetration testing doesn’t cover prompt injection, data leakage, or hallucination risks.”
We run a comprehensive AI red-teaming exercise: prompt injection attacks, jailbreaking attempts, data extraction probes, and adversarial inputs. We document every vulnerability and harden the system before it faces real users.
AI chatbot launched with documented security testing, hardened against known attack vectors, and continuous monitoring in place.
Regulated organization with long-lived data
“We store financial and healthcare records for 20+ years. Our CISO read about quantum computing breaking encryption and wants a plan. We don’t know where to start.”
We inventory all cryptographic assets (certificates, keys, encrypted data stores), assess quantum vulnerability by data sensitivity and retention period, and build a phased PQC migration roadmap prioritized by risk.
Complete crypto inventory, quantum risk assessment, and multi-year PQC migration plan the CISO can present to the board.
Enterprise wanting AI-powered defense
“Our SOC is overwhelmed with alerts, 90% are false positives. We need AI to help us separate real threats from noise, but we don’t know which tools to trust or how to integrate them.”
We evaluate AI-powered security tools against your existing stack, implement ML-based anomaly detection and alert correlation, and optimize your SIEM to surface genuine threats while suppressing false positives.
SOC alert volume reduced by 60%. Mean time to detect real threats cut by 45%. Security team focused on genuine incidents instead of noise.
What you walk away with
Identity and access review
Who can reach what, including the accounts and service principals nobody remembers creating.
Zero Trust roadmap
Sequenced against your real systems, with the order to do it in and what to skip.
AI-agent identity model
How agents authenticate, what they may touch, and how you revoke it.
Access review process
Light enough that it still happens after we've gone.
Incident path
Who decides what, at what hour, agreed before it's needed.
Is your security posture ready for the AI era?
In a 30-minute AI security assessment call, we’ll review your AI deployment landscape, identify your most exposed AI systems, and outline the security gaps between traditional AppSec and AI-specific threats. Whether you’re securing a chatbot, hardening an AI pipeline, or planning for post-quantum, we’ll give you a clear starting point.