LIVE
TEENAEGIS COMMAND™TAIM v1
GLOBAL RISK: SEVERE
Updated 4:19:49 PM
Methodology Protected

Layer 0 — Live Signal Feed

Incident Feed
HIGH

Sextortion — Instagram

California · 4/5/2026

IF-2026-0405
CRITICAL

Grooming — Discord

Texas · 4/4/2026

IF-2026-0404
HIGH

Self-harm content — TikTok

Florida · 4/3/2026

IF-2026-0403
SEVERE

Off-platform migration — Roblox → Telegram

New York · 4/2/2026

IF-2026-0402
HIGH

Sextortion — Snapchat

Illinois · 4/1/2026

IF-2026-0401
Drift Monitor
73.4
Drift Velocity Index
↑ ACCELERATING
Worst PlatformTikTok
Avg Time to Harm11 minutes
Platform Radar
Meta
78
TikTok
82
Snap
71
Discord
84
X
88
Vulnerability Heatmap — Cohort Targeting Spikes
LGBTQIA+ teens
84.3
↑ risingInstagram
Neurodivergent teens
79.6
↑ risingDiscord
Socially isolated teens
77.4
→ stableRoblox
High-achievement pressure teens
61.2
↑ risingTikTok

AI Intelligence Layer — LLM Signal Sources

Cross-validated across 6 frontier models

TeenAegis cross-validates threat intelligence across six frontier AI models to eliminate single-model bias, hallucination risk, and coverage gaps. Each model contributes distinct signal types. Consensus scoring requires agreement from at least 4 of 6 models before a threat pattern is elevated to the TAIM stack.

xAI Grok
LIVE
xAI (Elon Musk)
Real-time social signal analysis
Platform trend detection, viral harm pattern recognition, X/Twitter threat feeds
Claude 3.5 Sonnet
Anthropic
Legal & policy document analysis
Legislative text parsing, court document analysis, regulatory gap identification
GPT-4o
OpenAI
Multi-modal threat classification
Image/video harm classification, grooming pattern detection, behavioral analysis
Gemini 1.5 Pro
Google DeepMind
Global data synthesis
Cross-language threat monitoring, international incident correlation, CSAM trend analysis
Llama 3.1 405B
Meta AI
Open-source validation layer
Independent cross-check, bias detection, methodology audit, reproducibility verification
Mistral Large
Mistral AI
EU regulatory intelligence
DSA/GDPR compliance monitoring, European enforcement actions, OFCOM analysis
6
Frontier Models
4/6
Consensus Threshold
~0%
Single-Model Bias Risk

Layer 1–4 — Intelligence Engines

EXPOSURE ENGINE

How kids are led into harm — Algorithmic Drift · Content Adjacency · Platform Penetration

67.9
F
Algorithmic Drift Score (ADS)F
69.3↑ +3.2

Ofcom 2024 §4.2 · Stanford IO 2023

Content Adjacency Index (CAI)F
65.9↑ +2.1

Stanford IO 2023 · DSA Transparency 2024

Platform Penetration Rate (PPR)F
68.4→ +0.4

Pew Research 2024 · Common Sense 2023

What this proves: Harm is not random. It is engineered proximity. Platforms design recommendation systems that accelerate the journey from safe to harmful content — average drift time is 11 minutes on the worst-performing platform.

Layer 5 — Decision Support

Priority Alerts
CRITICAL

Entrapment velocity accelerating — Bay Area cohort, Discord → Telegram migration detected

NCMEC pattern analysis

HIGH

Platform response lag exceeding 72-hour threshold on X — repeat offender survival rate 83%

IWF 2024 · FTC records

HIGH

LGBTQIA+ targeting efficiency spike — Instagram identity signal amplification +4.7 pts

Thorn 2023 §3.1

Recommended Interventions
Parent

Initiate open conversation about platform migration patterns — average awareness lag is 4.7 days

HIGH
School

Activate sextortion response playbook for Bay Area cohort — incident clustering detected

HIGH
Platform

Escalate X repeat offender survival rate to FTC — 83% survival rate exceeds negligence threshold

CRITICAL
Response Playbooks
Sextortion Response Protocol
7 stepsACTIVE
Grooming Interruption Guide
5 stepsACTIVE
School-Level Intervention
6 stepsACTIVE
Off-Platform Migration Alert
4 stepsACTIVE
Scenario Modeling
No intervention — current trajectory78%

Escalation to off-platform coercion within 30 days

Parent awareness within 48 hours34%

Escalation probability reduced by 56%

Platform removes offender within 24 hours19%

Escalation probability reduced by 74%

Layer 6 — After Action / Memory

Incident Timeline

4/5/2026

Sextortion — Instagram

California · FBI IC3 pattern analysis

4/4/2026

Grooming — Discord

Texas · NCMEC CyberTipline

4/3/2026

Self-harm content — TikTok

Florida · Ofcom 2024 §4.2

4/2/2026

Off-platform migration — Roblox → Telegram

New York · Europol IOCTA 2024

4/1/2026

Sextortion — Snapchat

Illinois · Thorn 2023 §3.1

Evidence Archive — Litigation-Ready Sources

NCMEC-2023

CyberTipline Annual Report 2023

Government

FBI-IC3-2023

IC3 Annual Report 2023

Government

THORN-2023

Sextortion of Minors Report

NGO Research

IWF-2024

Internet Watch Foundation Annual Report 2024

NGO Research

OFCOM-2024

Online Safety Report 2024

Regulatory

EUROPOL-2024

IOCTA 2024 — Online Child Sexual Exploitation

Law Enforcement

TeenAegis Intelligence Model (TAIM) v1 — Methodology Statement. All indices are computed from publicly available, government-published, peer-reviewed, and court-verified datasets. Source citations are available to verified researchers, regulators, and legal counsel on request. Scoring methodology is proprietary to TeenAegis and is not disclosed in this interface. All data is presented for intelligence and policy purposes. Nothing in this interface constitutes legal advice. © TeenAegis 2026. Unauthorized reproduction, scraping, or systematic extraction of this data is prohibited.

Global Risk Level
SEVERE
Score: 67.2 / 100
Intervention Clock
113h
Average parent awareness lag
Source: Thorn 2023 §5.2
Top Threats
#1

Entrapment via identity-affirming grooming

#2

Algorithmic drift into self-harm content

#3

Off-platform migration to encrypted channels

Most Exposed
LGBTQIA+ teens aged 13–16
TEI: 84.3 / 100
Worst Platform
X (Twitter)
PNI: 92.0 / 100
TAIM Stack
Composite Score67.2