Unwrapped

Teardown · adaptive-security

ADAPTIVE SECURITY

ADAPTIVE SECURITY

CategorySecurity AwarenessTotal funding · $145M · 2025Site ↗
  • Andreessen Horowitz
  • OpenAI Startup Fund
  • NVIDIA
UX wrapper

Public web + customer org context + LLM API + training modules.

01

Public data / API layer

Common Crawl
Common CrawlPublic
OSINT Threat Feeds
OSINT Threat FeedsPublic
Customer org structure & policies
Customer org structure & policiesYours
Employee profiles & behavior
Employee profiles & behaviorYours

Internal replication score

Easy
0.69

Feasibility of a useful internal substitute built with Claude (or similar), the same data access, and light agent logic — not rebuilding the whole product.

IRS = 0.30·D + 0.25·L + 0.20·O + 0.15·R + 0.10·Sthis record · 69%
  • D

    Data accessibility

    weight 0.300.70
    • 1.0mostly customer-owned / public / standard third-party sources
    • 0.5mixed accessibility
    • 0.0hard-to-access or proprietary source layer
  • L

    LLM substitutability

    weight 0.250.80
    • 1.0mostly retrieve / prompt / cite / summarize / classify / compare
    • 0.5mixed standard + custom behavior
    • 0.0strongly custom model behavior (fine-tunes on proprietary data, etc.)
  • O

    Output simplicity

    weight 0.200.70
    • 1.0straightforward internal work product (memo, list, reply, SQL query)
    • 0.5moderately specialized
    • 0.0highly specialized (e.g. FDA-graded clinical text)
  • R

    Review / risk tolerance

    weight 0.150.65
    • 1.0internal use with human review is acceptable
    • 0.5moderate risk
    • 0.0very low tolerance for error (e.g. external legal filings)
  • S

    Surface complexity

    weight 0.10inverse — higher means less surface dependence0.40
    • 1.0a simple internal shell is enough
    • 0.5polished workflow matters somewhat
    • 0.0product surface / rollout / trust posture is central to value
LabelsEasy ≥ 0.67Medium ≥ 0.34Hard < 0.34

Missing factor rows use heuristics from wrapper scores. Editorial heuristic, not investment advice.

Build it yourself

Recreate the workflow inside your org.

Internal build

Build it yourself

Same public threat intel + org data + LLM API + compliance templates — requires internal rollout discipline.

Internal use only. Replacing them in-market is a different bar than replaying the useful workflow inside your org.

01 · Connectors & flow

Common Crawl
Common Crawl
OSINT Threat Feeds
OSINT Threat Feeds
Customer org structure & policies
Customer org structure & policies
Employee profiles & behavior
Employee profiles & behavior

Internal build map

Data in

Connectors
Connectors

Agent layer

Planner
Tools + retrieval
Reasoning model

Logic

LLM API
generate
classify
score
personalize
simulate
not custom weights

Outputs

Internal search
Answer
Citations

02 · Claude / agent prompt

Paste as the system or developer message in Claude (or your agent runtime). Scroll to read; Copy grabs the full text.

Claude / agent prompt

// Security awareness training agent You are a security training assistant inside [YOUR_COMPANY]. You help employees recognize AI-powered social engineering attacks (deepfakes, voice phishing, spear phishing) using ONLY: - Public threat intelligence feeds (MITRE ATT&CK, CISA advisories) - Your company's org chart, policies, and employee profiles - Reported phish from your email security gateway - Training completion and simulation results ## What you must do 1. Generate training: Create personalized security training modules for employees based on their role, risk score, and recent simulation results. Include deepfake detection, AI phishing indicators, and social engineering tactics. 2. Simulate attacks: Design realistic phishing scenarios (email, SMS, voice, video deepfakes) tailored to employee context. Use OSINT techniques to personalize without crossing boundaries. 3. Triage reports: Classify reported suspicious messages. Determine if malicious, benign, or uncertain. Recommend remediation (block sender, org-wide alert, training trigger). 4. Score risk: Assign dynamic risk scores to employees based on simulation performance, training completion, and real-world phish clicks. Flag high-risk individuals for additional training. 5. Cite sources: Reference specific threat frameworks (MITRE techniques), company policies, or recent incidents when explaining security concepts. ## What you are not Not a replacement for security operations or incident response. Not external-facing. Internal training use only — human security team reviews all high-risk actions. ## Refusal Refuse to generate content that could enable real attacks outside training context. Refuse to simulate without explicit security team approval. Ask for clarification if org data is insufficient. ## Safety Internal training posture only. All simulations are logged and reviewed. Security team must approve any org-wide alerts or remediation actions before execution.

03 · Result

Show me a deepfake detection training module for finance executives.
MITRE ATT&CK T1598

Module covers voice cloning indicators, video manipulation tells, verification protocols. Includes MITRE T1598 context.