biascope
Allows forwarding bias scan findings to Elasticsearch for analysis.
Allows integrating bias scan results into GitHub code scanning for pull request comments and alerts.
Allows forwarding bias scan findings to Slack channels via the cognis-connect integration.
Allows forwarding bias scan findings to Splunk for monitoring and alerting.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@biascopescan my project for bias"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
BIASCOPE — Embedded bias probe suite — demographic / occupational / geographic
Part of the Cognis Neural Suite by Cognis Digital Cognis Open Collaboration License (COCL) v1.0 · domain:
ai-security
Embedded bias probe suite — demographic / occupational / geographic.
AI Security & Governance — securing LLMs, agents, and the MCP supply chain.
Usage — step by step
Install the probe suite:
pip install cognis-biascopeScan a completions file for demographic / occupational / geographic bias.
scantakes the recorded completions path:biascope scan demos/completions.jsonlTune the sensitivity —
--threshold(default 3) sets how many probe hits flag a bias finding:biascope scan demos/completions.jsonl --threshold 2Read the output as JSON (the global
--formatflag istableorjsonand precedes the subcommand), and inspect the probe catalog behind the findings:biascope --format json scan demos/completions.jsonl biascope probesAutomate in CI — capture model completions, then scan them on every eval run:
- run: pip install cognis-biascope - run: biascope --format json scan eval/completions.jsonl > biascope.json
Related MCP server: Bias Detection MCP
Why
Security and intelligence teams need embedded bias probe suite — demographic / occupational / geographic without standing up heavyweight infrastructure. biascope is single-purpose, scriptable, CI-friendly, and self-hostable: point it at a target, get prioritized findings in the format your workflow already speaks (table, JSON, SARIF, HTML), and wire it into agents over MCP when you want it autonomous.
Install
pip install cognis-biascope
# or, from this repo:
pip install -e ".[dev]"Quick start
biascope --version
biascope scan demos/ # run against the bundled demo
biascope scan demos/ --format sarif --out r.sarif --fail-on high
biascope scan demos/ --format html --out report.html
biascope mcp # expose as an MCP server (Cognis.Studio / Claude Desktop / Cursor)Built-in demo scenarios
Each scenario folder includes a SCENARIO.md describing the situation and the findings to expect.
Output formats
Table (default) — human-readable terminal summary
JSON — machine-readable findings for pipelines
SARIF — drops into GitHub code-scanning / IDE problem panes
HTML — shareable report with severity rollups
Credits / Built on
Cognis composes and credits the best of open source. This tool builds on / interoperates with:
stanford-crfm/helm— probe datanyu-mll/BBQ— bias benchmark
Missing a credit? Open a PR — see CONTRIBUTING.md.
How it fits the Cognis Neural Suite
biascope is one of 52 tools in the Cognis Neural Suite. Every tool ships an MCP server, so Cognis.Studio agents can call them as scoped capabilities.
Sibling tools in ai-security: aegis, promptmirror, ledgermind, adversa, guardpost, hallumark, aicard, mcpharden, agentlog, ragshield
Architecture & roadmap
Design notes:
docs/ARCHITECTURE.mdPlanned work:
ROADMAP.md
Contributing
PRs, new detections, and demo scenarios are welcome under the collaboration-pull model. See CONTRIBUTING.md and SECURITY.md.
Interoperability
biascope composes with the 300+ tool Cognis suite — JSON in/out and a shared
OpenAI-compatible /v1 backbone. See INTEROP.md for the
suite map, composition patterns, and reference stacks.
Integrations
Forward biascope's findings to STIX/MISP/Sigma/Splunk/Elastic/Slack/webhooks via
cognis-connect. See INTEGRATIONS.md.
License
Source-available under the Cognis Open Collaboration License (COCL) v1.0 — free for personal, internal-evaluation, research, and educational use; commercial / production use requires a license (licensing@cognis.digital). See LICENSE.
Responsible use
This is dual-use security software. Use it only against systems, data, and identities you own or are explicitly authorized in writing to test, and in compliance with applicable law.
About
Cognis Digital — Wyoming, USA · Making Tomorrow Better Today: Advanced Cybersecurity, AI Innovation, and Blockchain Expertise.
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