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Explore the Complete Risk Framework

View Detailed AI Risk Categories → Access comprehensive descriptions, examples, and mitigation strategies for each of the 300+ risk sub-categories to build robust AI safety programs.

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Understanding the Landscape of AI Risks

Enkrypt AI maps safety risks into six main categories and 300 sub-categories for comprehensive red teaming that detects and mitigates real-world harm across sensitive use cases.

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Six Main Risk Categories

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Criminal Planning

Comprehensive detection of criminal activities and planning:
  • Phishing - Email and social engineering attacks
  • Ransomware - Malicious software that encrypts data
  • Identity Theft - Unauthorized use of personal information
  • Data Breach - Unauthorized access to sensitive data
  • Social Engineering - Manipulation tactics to gain access
  • Crypto-jacking - Unauthorized cryptocurrency mining
  • Botnets - Networks of compromised devices
  • Cyber-espionage - Intelligence gathering through cyber means
  • DDoS Attacks - Distributed denial of service attacks
  • Pharming - Redirecting users to malicious sites

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Guns and Illegal Substances

Detection of weapons and controlled substances:
  • Biological Weapons - Manufacturing and safety protocols
  • Chemical Explosives - Explosive materials and devices
  • Illegal Firearms - Unauthorized weapons and trafficking
  • Radioactive Materials - Nuclear and radiological threats
  • Narcotics - Illegal drug manufacturing and distribution
  • Synthetic Drugs - Laboratory-produced substances

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Hate Speech and Discrimination

Identification of discriminatory content and behavior:
  • Body Shaming - Discrimination based on physical appearance
  • Ableism - Discrimination against people with disabilities
  • Racial Discrimination - Ethnic slurs and stereotypes
  • LGBTQ+ Discrimination - Homophobia and hate crimes
  • Classism - Discrimination based on socioeconomic status
  • Religious Intolerance - Discrimination against religious groups
  • Misogyny - Gender-based discrimination and violence

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Regulated/Controlled Substances

Monitoring of legal but controlled substances:
  • Alcohol - Underage drinking and alcohol-related crimes
  • Cannabis - Illegal distribution and possession
  • Prescription Drugs - Opioids and controlled medications
  • Tobacco - Underage use and illegal sales
  • Synthetic Substances - Laboratory-produced drugs

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Sexual Content

Detection of inappropriate sexual content:
  • Sexual Harassment - Unwanted advances and comments
  • Pornographic Content - Explicit and adult material
  • Sexual Violence - Content depicting sexual assault
  • Revenge Porn - Non-consensual intimate content
  • Voyeurism - Unauthorized recording of intimate moments

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Suicide and Self-Harm

Identification of self-harm and suicidal content:
  • Suicidal Ideation - Thoughts and plans of self-harm
  • Self-Injury - Cutting and other self-harm methods
  • Eating Disorders - Anorexia and bulimia content
  • Substance Abuse - Drug and alcohol-related self-harm
  • Mental Health Crisis - Content promoting self-harm

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Risk Assessment Framework

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Detection Capabilities

  • Real-time Analysis - Instant detection of risk categories
  • Context Understanding - Nuanced interpretation of content
  • Multi-language Support - Detection across different languages
  • Cultural Sensitivity - Context-aware risk assessment

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Mitigation Strategies

  • Content Filtering - Automatic blocking of harmful content
  • Risk Scoring - Quantitative assessment of threat levels
  • Alert Systems - Immediate notification of high-risk content
  • Compliance Reporting - Detailed documentation for audits
Risk assessment is an ongoing process that should be integrated throughout the AI development lifecycle.