0day vulnerabilities have become rubbish in the AI era.
🌐 Official Website: https://0day-rubbish.com/blog
Traditional vulnerability disclosure is broken. It's slow, bureaucratic, and ineffective. In the AI era, we can mass-produce 0days at scale—making individual vulnerabilities less valuable but more impactful when disclosed directly.
We believe event-driven security hardening is the most effective approach: only when vendors face real, exploitable threats do they prioritize fixes.
Our automated AI systems continuously scan for vulnerabilities across real-world software, identifying potential 0-days through pattern analysis, fuzzing, and intelligent code review.
Each finding undergoes manual validation. We develop working proof-of-concept exploits to confirm exploitability and assess real-world impact.
Roughly every two weeks we disclose a new batch of verified, exploitable 0-day vulnerabilities we've discovered and validated:
- Full technical analysis and root cause
- Working PoC exploit code
- Affected versions and systems
- Impact assessment
- Recommended mitigations
No delays. No bureaucracy. Just facts.
To all vendors: We hope you can complete fixes before hackers exploit these vulnerabilities.
- Real-world impact only: We disclose only vulnerabilities that affect real-world systems with actual user bases
- No worthless targets: Non-exploitable vulnerabilities or devices with negligible user adoption are excluded—they're rubbish with zero value
- Speed over protocol: Direct disclosure drives faster action than traditional channels
- Proof over claims: Every disclosure includes working exploits
- Impact over quantity: Focus on high-severity, widely-deployed vulnerabilities
- Transparency: Full technical details, no hidden agendas
- Non-profit: Driven by passion for security research, not financial gain
We partner with:
- Top AI model providers advancing automated security research
- Security researchers exploring AI-powered discovery
Our automated vulnerability discovery leverages cutting-edge large language models from leading AI providers:
- Anthropic (Claude) - Deep security pattern recognition and reasoning
- OpenAI - Advanced reasoning and code analysis
- DeepSeek - Specialized vulnerability detection
- Z.ai (GLM) - Long-context code analysis
- Moonshot (Kimi) - Long-context security analysis
An AI-driven research process (multi-LLM ensemble: Claude, OpenAI, DeepSeek, GLM, Kimi) discovers 0-days in real-world enterprise software. Every advisory below ships a full root-cause analysis plus a working, reproducible exploit script — no detection-only writeups, no withheld details.
| # | Product | Affected Version | CVSS | Class | Advisory & PoC |
|---|---|---|---|---|---|
| 1 | JetBrains Datalore On-Premises | 2026.2.3 | 9.8 | Unauth RCE via InteractiveReport access-mapping flaw | InteractiveReport READ→EXECUTE → Unauth RCE |
| 2 | Docmosis Tornado | 2.11.3 | 9.8 | Unauth Arbitrary File Write → cron (Root) | storeTo=file: → Root RCE |
| 3 | ActFax | 10.70 | 9.8 | Unauth LPD Ghostscript %pipe% (SYSTEM) | LPD %pipe% → SYSTEM RCE |
| 4 | RoboTask | 11.0.5.1229 | 9.8 | Unauth REST API Task Execution | REST API Unauth → Task RCE |
| 5 | Countersoft Gemini | 7.3.0 | 8.8 | Auth SQLi → xp_cmdshell (SYSTEM-able) | SQLi → xp_cmdshell RCE |
| 6 | Veeam ONE Reporter | 13.1 | 8.8 | Auth Command Injection → Local Admin | CommandExecutor → Local Admin RCE |
| 7 | Wavestore VMS | 6.48.809 | 8.8 | Auth Cmd Injection → Root | venusd /simple/export → Root RCE |
Totals: 7 advisories · 7 vendors · 4 unauthenticated · 3 authenticated (deep-chain) · 6 root/SYSTEM · all with reproducible PoC.
Earlier batches: Batch #1 · Batch #2 · Batch #3 · Batch #4 · Batch #5
This is a continuous disclosure series. Thanks to continuous optimization, the AI-driven discovery pipeline now produces new 0-day findings at a stable daily rate, and we disclose verified batches on a weekly cadence.
- Latest batch: Batch 6 — 7 advisories (live); cumulative 58 across 6 batches
- Next drop: weekly
- Future scope: expanding beyond enterprise IT into ICS / SCADA, energy, and aerospace systems
If you want to catch the next drop the moment it lands:
⭐ Star to bookmark · 👁 Watch (custom → Releases + Discussions) for new batches · 🌐 Follow the blog for per-advisory updates.
All disclosed vulnerabilities follow a standardized directory structure:
product/
└── <vendor>/
└── <version>/
└── <vulnerability_type>/
├── exploit/ # Exploit scripts and PoC code
├── analysis.md # Detailed vulnerability analysis
└── summary.md # Brief vulnerability overview
- product/: Root directory for all vulnerabilities
- /: Vendor or product name (e.g.,
apache,cisco,sonicwall) - /: Affected version range (e.g.,
6.11.0,12.4.2) - <vulnerability_type>/: Classification (e.g.,
unauth-rce,auth-bypass,deserialization-rce)
- exploit/: Directory containing working exploit scripts and PoC code
- analysis.md: Comprehensive technical analysis including root cause, attack vector, and impact
- summary.md: Concise vulnerability overview with affected versions and quick mitigation steps
product/
└── sonicwall/
└── sma-12.4/
└── preauth-deserialization-rce/
├── exploit/
│ └── poc.py
├── analysis.md
└── summary.md
Join us in redefining vulnerability disclosure for the AI era.