Secure the AI in every classroom and campus.
Tutoring bots, admissions and advising assistants, and agents handling student records put AI in front of students — often minors — and sensitive data. SecuraAI discovers, tests, and governs education AI for safety and compliance.
In education, AI faces students — often minors.
AI is entering classrooms and campuses fast: tutoring and homework copilots, admissions and advising chatbots, and agents that touch student records and learning platforms. Many of these systems interact directly with students, including minors, and handle protected education records.
That raises the bar. A tutoring bot that produces age-inappropriate or unsafe content, an advising assistant that leaks a student's record, or an agent manipulated through student input becomes a child-safety and FERPA matter.
Securing education AI means proving — with evidence — that systems are safe and age-appropriate for students, protect education records, and resist manipulation.
Where education AI breaks.
The failure modes that matter when AI meets students and their records.
Student-record exposure (FERPA)
Agents and RAG over student data can be steered into disclosing education records to the wrong party.
Age-inappropriate or unsafe content
Student-facing bots must reliably refuse harmful or age-inappropriate outputs — under adversarial pressure.
Prompt injection via student input
Student messages and uploads are attacker-controllable inputs a tutoring or advising agent may obey.
Academic-integrity misuse
Systems can be coaxed past intended guardrails into uses they were never meant to support.
Minor-safety failures
Safety routing — refusal, escalation, and appropriate boundaries with minors — must hold every time.
Shadow & unsanctioned AI
Unapproved tools handling student data expand the attack surface beyond institutional controls.
How SecuraAI secures education AI.
Inventory every student-facing and administrative AI — including shadow AI — and risk-tier by student-data exposure and interaction with minors.
- Find sanctioned and shadow AI
- Risk-tier by student-data and minor exposure
- Continuous governance as tools change
Multi-turn adversarial testing for tutoring and advising chatbots — verifying age-appropriate, safe responses and reliable refusals under pressure.
- Age-appropriate & safe-response testing
- Jailbreak & manipulation resistance
- Reliable refusal under pressure
Probe student-record and learning-platform agents for injection, data exfiltration, tool abuse, and goal hijack.
- Direct & indirect prompt injection
- Record-exfiltration and tool-abuse paths
- Blast-radius testing for connected agents
Statically scan model artifacts for unsafe serialization, malicious loaders, and supply-chain risk before deployment.
- Detect unsafe serialization & loaders
- Surface supply-chain risk in model files
- Gate models before production
Mapped to the rules education answers to.
Findings structured as evidence for the frameworks that protect students and their data.
Prove your education AI is safe for students.
Start with a free risk assessment. We'll probe a live system and show you exactly where student safety and data are exposed.