โโโโโโโ โโโโโโโ โโโโโโโโ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โโโโโโโ โโโโ โโโ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โโโ
โโโโโโโโโโโโโโโโโโโโโโ โโโ โโโโโโ โโโโโโโโโโโโโโโโโโโโโโ โโโโโโโโโ โโโ
โโโโโโโ โโโโโโโโโโโโโโ โโโ โโโโโโ โโโโโโโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโ
โโโ โโโ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โโโโโโ
โโโ โโโ โโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โโโโโโโ โโโ โโโโโ
โ The Map Precedes the Territory โ
"The territory no longer precedes the map... It is the map that engenders the territory."
Predictive Threat Modeling - Threats that exist before they happen
Baudrillard's "precession of simulacra" describes how models now precede realityโthe map creates the territory. Precession applies this to threat modeling.
Traditional threat modeling: "What threats exist?" Precession: "What threats WILL exist when we build this?"
By modeling threats before systems exist, we create threats that are born into existence with their vulnerabilities already known.
- Design a system โ Model all possible threats
- Threats become real โ Because the system exists
- We predicted them โ Before they were threats
- The model preceded reality
| Traditional | Precession |
|---|---|
| System exists โ Find threats | Model threats โ System exists |
| Penetration testing | Threat anticipation |
| "What went wrong?" | "What will go wrong?" |
| Forensics | Prophecy |
Predict threats from architecture
precession oracle --architecture system.yaml- Analyzes system design before implementation
- Predicts attack vectors from components
- Generates threat timeline (what will be discovered when)
- Outputs pre-emptive mitigations
Model threats that don't exist yet
precession emergence --technology "quantum computing" --domain "finance"- Projects future threat landscapes
- Models attacks using technologies that don't fully exist
- Predicts exploit development timelines
- Generates defensive R&D priorities
Create the threat before it's real
precession territory --target competitor.com --scope ethical- Maps attack surface of target
- Predicts which vulnerabilities they'll discover
- Models their incident response
- Generates engagement timeline
Generate specific threat predictions
precession prophecy --system production-api --horizon 90d- Concrete predictions with confidence intervals
- Expected CVE timeline
- Attack probability modeling
- Defender preparation checklist
โโโโโโโ โโโโโโโ โโโโโโโโ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โโโโโโโ โโโโ โโโ
[FORESEEING] The map is being drawn...
โ THREAT PRECESSION REPORT โ
Target: New Financial API (pre-launch)
Architecture: microservices, Kubernetes, Go backend, React frontend
Analysis Date: 2026-02-03
Prediction Horizon: 180 days post-launch
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ PREDICTED THREAT TIMELINE โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ โ
โ Day 0-7: Launch โ
โ โ Automated scanners will find: exposed /metrics endpoint (94%) โ
โ โ Expected CVE publication: none (too new) โ
โ โ Attack probability: LOW โ
โ โ
โ Day 7-30: Discovery Phase โ
โ โ Researchers will report: JWT algorithm confusion (78%) โ
โ โ IDOR in user profile endpoint (82%) โ
โ โ Rate limiting bypass in login (67%) โ
โ โ Expected bug bounty submissions: 12-18 โ
โ โ
โ Day 30-90: Weaponization โ
โ โ PoC exploit for JWT issue (if unpatched): Day 45 ยฑ 10 โ
โ โ First automated exploitation attempt: Day 60 ยฑ 15 โ
โ โ Integration into exploit kits: Day 75 ยฑ 20 โ
โ โ
โ Day 90-180: Maturity โ
โ โ Nation-state interest probability: 23% โ
โ โ Data breach probability (if no patches): 67% โ
โ โ Compliance violation discovery: 89% โ
โ โ
โ Confidence: โโโโโโโโโโ 81% โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ SPECIFIC VULNERABILITY PREDICTIONS โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ โ
โ VULN-001: JWT Algorithm Confusion โ
โ Component: /api/auth/verify โ
โ Attack Vector: Change alg:RS256 to alg:HS256 โ
โ Discovery: Day 12 ยฑ 5 โ
โ CVSS Prediction: 8.1 (High) โ
โ Mitigation: Hardcode algorithm, reject others โ
โ Mitigation Cost: 4 engineer-hours โ
โ โ
โ VULN-002: IDOR in Profile Endpoint โ
โ Component: /api/users/{id}/profile โ
โ Attack Vector: Increment user ID โ
โ Discovery: Day 8 ยฑ 3 โ
โ CVSS Prediction: 6.5 (Medium) โ
โ Mitigation: Verify ownership, use UUID โ
โ Mitigation Cost: 8 engineer-hours โ
โ โ
โ VULN-003: GraphQL Introspection Exposure โ
โ Component: /graphql โ
โ Attack Vector: Query __schema โ
โ Discovery: Day 3 ยฑ 1 โ
โ CVSS Prediction: 4.3 (Medium) โ
โ Mitigation: Disable introspection in production โ
โ Mitigation Cost: 1 engineer-hour โ
โ โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ PRE-EMPTIVE ACTION PLAN โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ โ
โ BEFORE LAUNCH (Total: 24 engineer-hours) โ
โ โ Implement JWT algorithm pinning [4h] [Critical] โ
โ โ Add ownership verification to all endpoints [8h] [High] โ
โ โ Disable GraphQL introspection [1h] [Medium] โ
โ โ Add anomaly detection on auth endpoints [6h] [High] โ
โ โ Implement proper rate limiting [5h] [High] โ
โ โ
โ Investment: 24 hours now โ
โ Saves: ~340 hours incident response + reputational damage โ
โ ROI: 1,316% โ
โ โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ PROPHECY SUMMARY โ
Predicted vulnerabilities: 7
Critical pre-launch fixes: 3
Expected CVEs prevented: 2
Breach probability reduction: 67% โ 12%
"The future is already hereโit's just not evenly distributed."
git clone https://github.com/bad-antics/precession
cd precession
pip install -e .
precession --awaken