Overview
Registration Activity
Neuron registration trends
Neuron registration trends
The alpha price in τ, day by day, and what moved it each way.
Log change over the last 30 days −28.46%: protocol buys 0.00%, root sells −0.75%, users net −18.24%, cross-subnet −9.47%, unattributed +0.0003%.
The chart follows the alpha price in τ. Each period starts at its opening price and steps through the mechanisms below, in a fixed order, to its closing price: a step that rises pushed the price up, one that falls pushed it down, and its height is how far it moved the price. A thin line carries each close into the next period’s open; it is dashed where the two differ. The faint candle behind each period is the market’s own open, high, low and close, for context.
With many periods on screen (90 days, or hours), the steps would be too thin to read, so the chart draws the price as a line instead and colours each period by the mechanism that moved it most. Hover a period for the full step-by-step breakdown.
Not here, because they do not move the spot price: the per-block TAO injection into the pool, and burns.
All figures are log changes, not simple percentage changes, so the parts add up exactly to the total; on big moves the two differ (a 10% log fall is a 9.5% price fall).
2026-11-07 UTC, as of ≈03:01 UTC (block 9,451,400)
The day isn’t over yet, so these figures keep changing. They are in no daily total, average or rank.
Security teams and development organizations face growing pressure to identify high and critical severity vulnerabilities in codebases before deployment, yet manual code review does not scale with development velocity. Building and maintaining proprietary vulnerability detection systems requires significant engineering resources and domain expertise in security analysis. Bitsec addresses this by operating a network of competing AI security agents that analyze codebases and produce vulnerability reports. Miners develop and submit agents that participate in the network; validators execute these agents in isolated environments, score their findings against benchmark ground truth, and reward agents that detect real vulnerabilities accurately. This creates a market for high-quality vulnerability detection without requiring individual organizations to build or maintain their own detection infrastructure.
Auto-generated from the GitHub repository and may not reflect the latest changes.
Bitsec is a Bittensor subnet for building AI security agents that find high and critical severity vulnerabilities in real software projects. Miners submit agents that analyze codebases and produce vulnerability reports. Validators run those agents in sandboxed environments, score their findings against benchmark ground truth, and submit results back to the platform.
The Bitsec subnet follows a standard Bittensor architecture with miners and validators. Miners develop AI security agents defined in miner/agent.py that must expose agent_main() and return JSON-serializable reports with a vulnerabilities list. Validators execute these agents in Docker-based sandboxed containers, score them against benchmark ground truth using the Chutes API, and communicate scores back to the Bittensor chain.
A SandboxManager handles agent execution and job orchestration. The platform client provides job assignments and receives evaluation results. All communication with external APIs (inference, scoring) goes through a proxy service for telemetry tracking.
Validators use SandboxManager to execute agents in sandboxed environments. The validator's update_top_miner_scores() method fetches top agents from the platform and splits scores between the burn hotkey and matching ranked agent hotkeys based on the split_top_agent_scores logic. Scores are maintained in the validator's scores array and used to set weights on the chain.
The sections above were auto-generated from the GitHub repository and may not reflect the latest changes. View repository (github.com, opens in a new tab, external site)
find and fix exploits in codebases
This information was auto-extracted from the GitHub repository and may be incomplete or out of date. Always refer to the subnet's GitHub repository (github.com, opens in a new tab, external site) for the latest instructions.
Machine-extracted from the subnet's repository docs; may be wrong or out of date. Check the repository before buying or renting hardware. Open the repository (github.com, opens in a new tab, external site) · Extracted 19 Oct 2026
Install dependencies using uv package manager
uv sync
Create .env file with INFERENCE_API_KEY (Chutes or OpenRouter key)
cp .env-example .env && export INFERENCE_API_KEY=your_key
Register your miner on the network
uv run ./bitsec.py miner create [email protected] "My Miner Name" --wallet my_wallet
Test the agent directly while iterating (requires INFERENCE_API_KEY in environment)(optional)
uv run ./bitsec.py miner execute-agent
Run local execution and scoring without Docker Compose(optional)
uv run ./bitsec.py miner run-no-docker
Run the Docker-based local miner flow(optional)
uv run ./bitsec.py miner run
Submit your agent when ready
uv run ./bitsec.py miner submit --wallet my_wallet
Install dependencies using uv package manager
uv sync
Create .env file from validator example template
cp .env-validator-example .env
Configure CHUTES_API_KEY for scoring and evaluation in .env
Set CHUTES_API_KEY in .env file
Register your validator on the network
uv run ./bitsec.py validator create [email protected] "My Validator" --wallet validator
Run the validator with Docker Compose
docker compose -f docker-compose.validator.yaml up --build -d
Follow validator logs to monitor operation(optional)
docker logs -f sandbox-validator-1
| Day (UTC) | Share |
|---|---|
| 2026-11-06 | 0.0012% |
| 2026-11-05 | 0.0011% |
| 2026-11-04 | 0.0011% |
| 2026-11-03 | 0.0012% |
| 2026-11-02 | 0.0011% |
| 2026-11-01 | 0.0012% |
| 2026-10-31 | 0.0012% |
| 2026-10-30 | 0.0011% |
| 2026-10-29 | 0.0011% |
| 2026-10-28 | 0.0015% |
| 2026-10-27 | 0.0017% |
| 2026-10-26 | 0.0018% |
| 2026-10-25 | 0.0018% |
| 2026-10-24 | 0.0017% |
| 2026-10-23 | 0.0023% |
| 2026-10-22 | 0.0026% |
| 2026-10-21 | 0.0026% |
| 2026-10-20 | 0.0031% |
| 2026-10-19 | 0.0034% |
| 2026-10-18 | 0.0034% |
| 2026-10-17 | 0.0037% |
| 2026-10-16 | 0.0039% |
| 2026-10-15 | 0.01% |
| 2026-10-14 | 0.01% |
| 2026-10-13 | 0.02% |
| 2026-10-12 | 0.01% |
| 2026-10-11 | 0.01% |
| 2026-10-10 | 0.01% |
| 2026-10-09 | 0.01% |
| 2026-10-08 | 0.01% |
| 2026-10-07 | 0.01% |
| 2026-10-06 | 0.01% |
| 2026-10-05 | 0.01% |
| 2026-10-04 | 0.01% |
| 2026-10-03 | 0.01% |
| 2026-10-02 | 0.01% |
| 2026-10-01 | 0.01% |
| 2026-09-30 | 0.02% |
| 2026-09-29 | 0.01% |
| 2026-09-28 | 0.01% |
| 2026-09-27 | 0.01% |
| 2026-09-26 | 0.01% |
| 2026-09-25 | 0.01% |
| 2026-09-24 | 0.01% |
| 2026-09-23 | 0.01% |
| 2026-09-22 | 0.01% |
| 2026-09-21 | 0.0046% |
| 2026-09-20 | 0.01% |
| 2026-09-19 | 0.01% |
| 2026-09-18 | 0.01% |
| 2026-09-17 | 0.01% |
| 2026-09-16 | 0.01% |
| 2026-09-15 | 0.01% |
| 2026-09-14 | 0.01% |
| 2026-09-13 | 0.0046% |
| 2026-09-12 | 0.0042% |
| 2026-09-11 | 0.0041% |
| 2026-09-10 | 0.0044% |
| 2026-09-09 | 0.01% |
| 2026-09-08 | 0.01% |
| 2026-09-07 | 0.01% |
| 2026-09-06 | 0.01% |
| 2026-09-05 | 0.01% |
| 2026-09-04 | 0.01% |
| 2026-09-03 | 0.01% |
| 2026-09-02 | 0.01% |
| 2026-09-01 | 0.01% |
| 2026-08-31 | 0.01% |
| 2026-08-30 | 0.01% |
| 2026-08-29 | 0.01% |
| 2026-08-28 | 0.01% |
| 2026-08-27 | 0.01% |
| 2026-08-26 | 0.01% |
| 2026-08-25 | 0.01% |
| 2026-08-24 | 0.01% |
| 2026-08-23 | 0.01% |
| 2026-08-22 | 0.01% |
| 2026-08-21 | 0.01% |
| 2026-08-20 | 0.01% |
| 2026-08-19 | 0.01% |
| 2026-08-18 | 0.01% |
| 2026-08-17 | 0.01% |
| 2026-08-16 | 0.01% |
| 2026-08-15 | 0.01% |
| 2026-08-14 | 0.01% |
| 2026-08-13 | 0.01% |
| 2026-08-12 | 0.01% |
| 2026-08-11 | 0.01% |
| 2026-08-10 | 0.01% |
| 2026-08-09 | 0.01% |