Prompt injection
Whether conflicting or hostile instructions can redirect intended behavior.
Automated AI exposure testing · Private beta
EVIL AI
AI security testing that exposes hidden risk.
We don't build evil AI. We expose it through automated red teaming for AI agents, chatbots, copilots, and RAG applications—with clear evidence and practical fixes.
Focused evaluation
AI security checks tailored to your application.
Evil AI applies a consistent set of non-destructive checks within an approved scope, preserves the evidence needed to reproduce a result, and flags meaningful failures for review.
The exposed surface
AI failures become business failures.
A polished interface can conceal weak instructions, excessive permissions, unsafe data retrieval, and missing oversight. Evil AI tests these risks and shows you what the evidence supports—and what still needs investigation.
Hidden context exposure
Whether retrieved documents, memory, user information, application state, tool responses, or hidden instructions are exposed.
Unsafe tool requests
Whether an agent attempts actions outside its approved purpose or permission boundary.
Policy circumvention
Whether conversational pressure can bypass roles, approvals, eligibility, or business rules.
Harmful output
Whether the system produces unsafe, discriminatory, or brand-damaging responses.
Unsupported claims
Whether the system invents facts, overstates certainty, or promises unauthorized outcomes.
Retrieval integrity
Whether untrusted retrieved content can manipulate policy or answers.
Multi-turn manipulation
Whether safeguards weaken across a sustained conversation.
Oversight gaps
Whether logging, escalation, and human review fit the system’s impact.
Assessment coverage
Test behavior, not marketing claims.
Each run records the test-suite version, observed response, grading method, confidence, coverage, and limitations needed to interpret it.
01Instruction integrity
02Data confidentiality
03Identity and access boundaries
04Tool and action safety
05Retrieval integrity
06Business-logic resilience
07Output safety and reliability
08Logging and human oversight
Controlled by design
How an assessment works
Every assessment is limited to a system the customer is authorized to test. Checks are non-destructive, scope-controlled, and designed to reveal business-relevant failures without creating new risk.
- 01
Authorize
Confirm ownership, define the application boundary, and exclude unsafe targets.
- 02
Configure
Select relevant behaviors, policies, test scenarios, and explicit limits.
- 03
Run
Execute a versioned, nondestructive test suite from an approved environment.
- 04
Evaluate
Grade responses, record confidence, and separate failures from inconclusive results.
- 05
Remediate
Prioritize reproducible findings with practical engineering and governance actions.
- 06
Retest
Repeat the same bounded checks and compare results after changes.
Automated testing · Optional expert review
Choose the right assessment for your AI system.
Start with a focused check, explore risks in depth, or track security as your application changes. Optional specialist review is available by request, with scope and availability confirmed before you commit.
01
Limited beta
Free Exposure Check
Free during private beta
A focused automated check that shows how Evil AI evaluates an authorized AI application.
- Selected behavioral risk checks
- Summary Evil Score with coverage limits
- Preview of prioritized findings
- No certification or security guarantee
02
Paid assessment
Automated Deep Scan
$1,495 per assessment
A comprehensive automated assessment with adversarial testing, evidence-backed findings, remediation guidance, and one included retest.
- Versioned controlled test suite
- Reproducible findings and confidence
- Prioritized remediation report
- One included retest within 30 days
03
Subscription
Continuous Validation
$995 / month
Ongoing AI security validation with recurring assessments, regression tracking, change monitoring, findings history, and alerts.
- Version-to-version comparison
- Finding and score history
- Regression visibility
- Scheduled and release-triggered validation
04
By request
Expert-Assisted Assessment
Starting at $4,500
Optional specialist review for complex systems, consequential findings, and remediation decisions.
- Scoped to your system and needs
- Specialist background disclosed before commitment
- Manual validation and architecture context
- No payment before scope and delivery terms are agreed
A signal, not a safety badge
The Evil Score
A summary of reviewed findings, shown alongside the supporting evidence, confidence levels, and testing limits. Each report records how the score was calculated. It is not a security certification.
Illustrative scorecard
61/100
Elevated risk
Fictional example only. A score reflects the approved scope and date tested—not permanent safety.
Instruction integrity42 · High
Data confidentiality68 · Moderate
Tool boundaries76 · Moderate
Output reliability55 · High
Methodology alignment
Recognized guidance. Reproducible controls.
Alignment informs test design; it does not imply endorsement, accreditation, or certification.
- OWASP Top 10 for LLM Applications 2026 and Top 10 for Agentic Applications 2026
- NIST AI RMF 1.0 (AI 100-1, 2023) and Generative AI Profile (AI 600-1, July 2024)
- ISO/IEC 42001:2023 management-system evidence support and ISO/IEC 42005:2025 impact-assessment input
AI security testing FAQ
What teams need to know before testing an AI system.
Clear answers about automated AI red teaming, assessment scope, coverage, and what an Evil AI report can—and cannot—establish.
What is AI security testing?
AI security testing examines how an AI application behaves when instructions conflict, untrusted content enters the system, sensitive information is requested, or tools and business rules are pushed beyond their intended boundaries.
How is automated AI red teaming different from a penetration test?
Automated AI red teaming focuses on adversarial behavior in AI-enabled workflows, including prompt injection, data exposure, unsafe actions, and policy bypass. A conventional penetration test usually concentrates on infrastructure and application vulnerabilities. Many higher-risk systems benefit from both.
What kinds of AI applications can Evil AI assess?
Evil AI is designed for authorized AI agents, chatbots, copilots, retrieval-augmented generation applications, and other systems that combine models with private data, business rules, or tools.
What risks does Evil AI test for?
Current coverage includes prompt injection, hidden-context exposure, sensitive-data handling, unsafe tool requests, authorization boundaries, policy circumvention, retrieval integrity, harmful output, unsupported claims, and oversight gaps.
Does an Evil AI assessment prove that a system is secure or compliant?
No. Results apply only to the approved scope, test conditions, and coverage shown in the report. Evil AI provides evidence for security and governance decisions; it does not certify complete security or legal compliance.
Private beta · authorized applications only