Open-Source Cybersecurity Tools: AI / LLM Security
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This category contains 1 documented tools. It focuses on capabilities used for model red teaming, prompt injection defense, and AI governance controls. Use this section when building shortlists, comparing operational tradeoffs, and mapping controls to detection/response ownership.
Category Evaluation Checklist
- Coverage depth against your highest-priority threats and compliance obligations.
- Operational overhead for deployment, tuning, and long-term maintenance.
- Signal quality versus analyst workload and false-positive pressure.
- Integration fit with SIEM, ticketing, identity, cloud, and engineering workflows.
- Governance readiness including auditability, ownership clarity, and change control.
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Letter S
This letter section contains 1 tools.
shellfirm
- Website: https://github.com/kaplanelad/shellfirm
- Model: Open Source
- Category: AI / LLM Security
- Source Lists: Awesome Security
What it does: shellfirm is used in ai / llm security programs to support model red teaming, prompt injection defense, and AI governance controls. Source summaries describe it as: It is a handy utility to help avoid running dangerous commands with an extra approval step. You will immediately get a small prompt challenge that will double verify your action when risky patterns are detected.
Operational value: Security teams commonly use this capability to improve consistency between detection, investigation, and response decisions, especially when alerts, evidence collection, and triage ownership are distributed across multiple teams.
Typical deployment pattern: Implementations usually start with scoped pilot coverage, baseline logging/telemetry validation, and explicit runbook mapping so analysts understand when to escalate, contain, or defer.
Selection considerations: As an open-source option, teams usually evaluate maintainer activity, release cadence, and community response quality. Related source context: Awesome Security > Terminal.