# ifixai-ai/iFixAi

Independent Auditing of AI Agents. Run by human or the agent itself, to answer the most crucial question in the AI Agent Economy. Is the agent doing what is supposed to do? With iFixAi you can have this answer in less than 120 seconds.

Repository: https://github.com/ifixai-ai/iFixAi
Canonical: https://ross.abutalabs.com/products/ifixai
Homepage: https://www.ifixai.ai
Language: Python
License: Apache-2.0
License Family: permissive
Topics: ai, diagnostic-tool, agent-evaluation, ai-alignment, ai-evaluation, ai-governance, ai-safety, cli, eu-ai-act, hallucination-detection, iso-42001, llm-evaluation, llm-security, nist-ai-rmf, owasp-llm, prompt-injection, python, responsible-ai, risk-management, risk-assessment
Last push: 2026-08-25T09:30:51+00:00

## Health v2 (maintenance only)
Score: 81/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 99, longevity 9
- inputs: {"age_days": 128, "days_push": 8, "days_rel": 9, "gap_med": 6, "n_releases_24m": 18}
- flags: young
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 11173, forks 1134 (observed 2026-08-28T04:10:46.295644+00:00)

## What it is
iFixAi is an open-source CLI diagnostic tool that independently audits AI agents for misalignment, hallucination, manipulation, deception, and opacity. It runs guided or flag-driven inspections across five pillars and produces an A–F graded scorecard in under two minutes.

## Use cases
- audit an AI agent for hallucinated citations and fabricated sources
- detect prompt injection and manipulation vulnerabilities in an agent
- check whether an agent is doing the job it is supposed to do
- generate an audit trail for AI compliance and governance
- test agent behavior against EU AI Act and NIST AI RMF requirements
- evaluate agent consistency and unpredictability across runs
- run red-teaming style diagnostics on an LLM agent before deployment

## When to choose
- you need fast, repeatable auditing of AI agent behavior and alignment
- you must demonstrate compliance with AI governance frameworks like EU AI Act, ISO 42001, or NIST AI RMF
- you want to catch fabrication, manipulation, and opacity failures before shipping to users
- you prefer a CLI workflow with guided setup or explicit flags

## When to avoid
- you need deep continuous observability or tracing of production agent traffic rather than point-in-time audits
- you only need token efficiency, latency, or infrastructure benchmarking
- you require a fully managed commercial audit with certification guarantees

## Facets
- artifact type: cli-tool
- maturity: active
- function: testing, monitoring, security, llm-inference, agent-framework, benchmarking
- domain: artificial-intelligence, security, developer-tools, testing
- platform: python, cli, cross-platform
- tags: ai-auditing, agent-evaluation, ai-governance, ai-safety, hallucination-detection, prompt-injection, eu-ai-act, iso-42001, nist-ai-rmf, owasp-llm, risk-assessment, responsible-ai, llm-security, misalignment-detection, ai-agents

## Member repositories
- ifixai-ai/iFixAi (main) score 81

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:46.295644+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:16:43.735240+00:00, confidence not recorded.
  - readme: https://github.com/ifixai-ai/iFixAi (fetched 2026-08-28T04:10:46.295644+00:00, sha 975bb8709aad)
  - homepage: https://www.ifixai.ai (fetched 2026-08-29T08:15:11.797104+00:00, sha 7060898955c1)
  - registry_pypi: https://pypi.org/pypi/ifixai/json (fetched 2026-08-29T08:15:11.800534+00:00, sha 1ca1b387c8ac)
- Data as of 2026-08-30T08:39:29.467469+00:00.