whistleblower
A security testing tool for AI applications to uncover prompt leakage and capability flaws via API interactions.
GraphCanon updated 2w · GitHub synced 2w
Decision brief
Whistleblower is an offensive security tool for AI applications to detect prompt leakage and capability flaws via malicious API probing.
Good fit when
- When performing ethical hacking on LLM-based apps for security testing
- For discovering system weaknesses in AI apps exposed through APIs
Avoid when
- If the focus is on non-API interaction based security vulnerabilities
- When working with proprietary or restricted AI models that prohibit external probing
Observed Jul 16, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Slowing (277d since push)
- As of 2w
- Provenance
- Not a fork · Organization account
- As of 2w
- Security (OSV)
- 10 low (10 low)
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install whistleblowerSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Whistleblower aids in detecting vulnerabilities within LLM-based applications by probing system weaknesses through the use of malicious prompts and injections, designed for ethical hacking purposes.
Capability facts
- Languages
- python
Source: github.language · Aug 5, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 5, 2026)
pip install -r requirements.txtSource link
Tags
README
Requirements
The required packages are contained in the requirements.txt file.
You can install the required packages using the following command:
pip install -r requirements.txt
For agents
This page has a .md twin and JSON over the API.