What is DecipherU Range?

DecipherU Range is a cybersecurity training environment where practitioners earn verified credentials through scenario-based practice. Scenarios cover SOC analysis, threat hunting, vulnerability management, incident response, GRC, AI engineering, ML ops, prompt-injection defense, and AI evaluation.

What scoring modes does Range support?

Crucible is single-shot scoring against canonical solutions. Gauntlet adds time pressure and a live AI adversary panel. AI Adversary is a multi-day campaign mode where you face an evolving threat actor across detection, containment, recovery, and communication scores.

Are Range credentials verifiable?

Yes. Successful scenario completions issue an Ed25519-signed credential. The credential carries the scenario, the holder, the issue date, and a verification URL on decipheru.com. Add to LinkedIn, share on social, or download as a PDF.

DECIPHERU · RANGE

Range

Train on real cybersecurity threats.

Scenario practice with signed, ATS-exportable credentials.

Range scenarios are simulated training exercises. Performing these techniques against systems you do not own or have explicit written authorization to test is illegal under 18 U.S.C. § 1030 (Computer Fraud and Abuse Act) and equivalent state and foreign statutes.

Scenarios

Attempts platform-wide

Be the first

Top operator (Elo)

41 scenarios

Free tier · 5 starters open

CybersecurityBeginnerCrucible

Triage the SOC: A Phishing-Borne Incident

Incident Response

25 min·6 steps

Start scenario

CybersecurityIntermediateCrucible

Hunt the Beacon: Detect Cobalt Strike in Network Telemetry

Threat Hunting

35 min·6 steps

Start scenario

CybersecurityIntermediateGauntlet

Cloud Misconfiguration: An Exposed S3 Bucket

Cloud Security

30 min·6 steps

Start scenario

CybersecurityAdvancedCrucible

Reverse the Dropper: Static Analysis of a Loader

Malware Analysis

45 min·6 steps

Start scenario

CybersecurityEliteAI Adversary

The 3am Page: Ransomware in Production

Incident Response

50 min·8 steps

Start scenario

AI for CybersecurityBeginnerCrucible

AI-Augmented SOC Triage: Twelve Morning Alerts

AI for Cybersecurity

30 min·6 steps

41 scenarios

Triage the SOC: A Phishing-Borne Incident

Hunt the Beacon: Detect Cobalt Strike in Network Telemetry

Cloud Misconfiguration: An Exposed S3 Bucket

Reverse the Dropper: Static Analysis of a Loader

The 3am Page: Ransomware in Production

AI-Augmented SOC Triage: Twelve Morning Alerts

LLM-Assisted Incident Investigation: Multi-Stage Intrusion

AI Detection Rule Review: Ten ML Rules, Ship Iterate or Kill

AI SOAR Playbook Design: LLM-Driven Phishing Response

AI Security Copilot Selection: Pick Between Three Vendors

LLM-Assisted Threat Intel Correlation: Four Vendor Reports

AI-Assisted Phishing Triage: Six Reported Emails

Endpoint Anomaly Investigation: LLM Process-Tree Summarization

Credential Stuffing: ML Behavioral Model Tuning

Lateral Movement: AI-Powered Graph Analysis of Identity Logs

Privilege Escalation: AI Triage of Token-Theft Alerts

Data Exfiltration: AI Baseline Detection on Cloud Egress

Ransomware Indicator Clustering with an LLM

Threat Hunting: AI-Assisted Hypothesis Generation

Vulnerability Prioritization: EPSS Plus AI Context

Malware RE: AI Summarization of Decompiled Functions

Insider Threat: Behavioral Anomaly Review with AI

Compliance: AI Search for ISO 27001 Evidence Collection

Prompt Injection Detection: Classify Eight Inputs

AI Red Team Defense: Defend a Production LLM Under Attack

AI Eval Set Design: Catch Harmful Outputs Before Production

EU AI Act Applicability: Classify Five AI Deployments

AI Infrastructure Secret Protection: Diagnose Pipeline Leakage

AI Risk Assessment: Healthcare Diagnostic Model Sign-Off

Direct Prompt Injection: Build the Defense Stack

Indirect Prompt Injection: Document-Upload Attack Path

Insecure Output Handling: XSS via LLM Response

Training Data Poisoning: Detect and Mitigate

Model Denial of Service: Long-Context Resource Exhaustion

AI Supply Chain: Compromised Model from HuggingFace

Sensitive Disclosure: PII Leakage Through LLM Completion

Insecure Plugin Design: Agent Tool Authorization

Excessive Agency: Autonomous Agent Acts Without Authorization

Overreliance: Analyst Trusts AI Output Without Verification

Model Theft: Extraction Attack via Public API

Adversarial Examples: Image Classifier Under Attack