autonoma-cli 0.1.0

Deterministic code security scanner. Detects and remediates hardcoded secrets.

Autonoma

Most secret scanners detect problems. Autonoma safely fixes them — or refuses when it cannot prove the change is safe.

Deterministic secret remediation with strict safety boundaries.

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Install

The open-source package is published to PyPI as autonoma-cli.

pip install autonoma-cli

Once installed, use the autonoma command:

autonoma --version
autonoma --help

Quick Example

Scan a project:

autonoma analyze ./your-project

Scan and apply safe fixes:

autonoma analyze ./your-project --auto-fix

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Example

Before

# settings.py

DATABASES = {
    "default": {
        "ENGINE": "django.db.backends.postgresql",
        "NAME": "prod_db",
        "USER": "admin",
        "PASSWORD": "Pr0d@ccess2024!",  # SEC001
        "HOST": "db.internal.company.com",
    }
}

SENDGRID_API_KEY = "SG.live-abc123xyz987_realkey"  # SEC002

After

# settings.py

import os

DATABASES = {
    "default": {
        "ENGINE": "django.db.backends.postgresql",
        "NAME": "prod_db",
        "USER": "admin",
        "PASSWORD": os.environ["PASSWORD"],
        "HOST": "db.internal.company.com",
    }
}

SENDGRID_API_KEY = os.environ["SENDGRID_API_KEY"]

Preview Fixes Safely

Preview fixes safely before applying them to guarantee deterministic outputs:

$ autonoma analyze demo-project --diff

- SENDGRID_API_KEY = "SG.live-abc123xyz987_realkey"
+ SENDGRID_API_KEY = os.environ["SENDGRID_API_KEY"]

Example CLI Output

$ autonoma analyze demo-project --auto-fix

Scanning 10 files...

SEC001  settings.py:8
Hardcoded password detected
Status: FIXED

SEC002  config.py:3
Hardcoded API key detected
Status: FIXED

SEC002  utils.py:14
Ambiguous secret pattern
Status: REFUSED

--------------------------------
Files scanned: 10
Issues detected: 3
Fixed: 2
Refused: 1

---

Commands

autonoma analyze PATH
autonoma analyze PATH --auto-fix
autonoma analyze PATH --diff
autonoma analyze PATH --json
autonoma analyze PATH --ci
autonoma history-scan PATH
autonoma --version

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CLI Features

Autonoma supports:

• --auto-fix — apply deterministic safe fixes
• --diff — preview proposed fixes as unified diffs
• --json — emit machine-readable output for automation
• --ci — use CI-oriented exit codes
• --quiet — minimize console output for pipelines
• --threads — parallelize scanning on larger repositories
• .autonomaignore — exclude noisy paths
• history-scan — detect secrets that still exist in Git history

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What Autonoma Detects

Code	Description
SEC001	Hardcoded passwords
SEC002	Hardcoded API keys
SEC003	High-risk SQL string construction
SEC004	Python SSTI patterns
SEC005	Insecure deserialization (pickle, unsafe yaml)

Auto-fix support:

Code	Behavior
SEC001	Auto-fixed when safe
SEC002	Auto-fixed when safe
SEC003–SEC005	Detection only

Autonoma deliberately avoids automatic rewrites for logic-level vulnerabilities.

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Safety Model

Autonoma only applies a fix when all three conditions are satisfied:

1. The transformation is structurally safe
2. The environment variable contract can be established
3. The modification introduces no ambiguity

Every finding produces one of four outcomes:

Status	Meaning
FIXED	Deterministic fix applied
REFUSED	Change declined to prevent unsafe modification
SKIPPED	Code already compliant
FAILED	Tool error

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Refusal Examples

Refusal is intentional. A wrong automated fix is worse than no fix.

No Environment Contract

API_KEY = "sk-live-abc123"

Refused because the project has no .env or dotenv dependency.

Ambiguous Variable Name

x = "sk-live-abc123"

Autonoma cannot safely infer an environment variable name.

Already Compliant

API_KEY = os.getenv("API_KEY", "sk-live-abc123")

Environment lookup already exists.

Ambiguous Secret Construction

token = "Bearer " + "sk-live-abc123"

Literal cannot be safely isolated.

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Git History Scanning

Autonoma can also detect secrets that were committed in the past and later removed from the working tree.

autonoma history-scan .

This helps identify secrets that still exist in Git history and may remain accessible through old commits, forks, mirrors, or cloned repositories.

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Why Autonoma Exists

Most security scanners stop at detection. Developers still need to manually remove secrets from code.

Autonoma focuses on deterministic remediation — automatically fixing the subset of issues that can be proven safe.

If safety cannot be guaranteed, it refuses the change instead of guessing.

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What Autonoma Deliberately Does NOT Do

Autonoma intentionally avoids features that cannot be made deterministic.

It does not perform:

• full taint analysis
• full data flow analysis
• automatic SQL injection rewriting
• automatic SSTI remediation
• LLM-generated patches

Only transformations that can be proven safe are applied automatically. Everything else is flagged for human review.

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CI Example

Autonoma can run directly in CI pipelines.

- name: Install Autonoma
  run: pip install autonoma-cli

- name: Scan repository
  run: autonoma analyze . --ci

Exit codes:

• 0 — no issues found
• 1 — issues found, but none are automatically fixable
• 2 — fixable issues found
• 3 — internal error

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Architecture

Autonoma is a local-first security remediation tool.

Key characteristics:

• Python 3.10+
• AST-based secret detection and remediation
• deterministic code transformations
• no telemetry
• no cloud dependency
• no LLM usage

All analysis runs entirely on the local machine.

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Validation

Autonoma has been tested across synthetic repositories, seeded secret datasets and real-world open-source Python projects containing exposed credentials.

Current validation results:

• 0 crashes across tested repositories
• 0 syntax breakage after auto-fix
• deterministic output across repeated runs
• idempotent fixes on rerun
• dry-run and diff preview do not modify files

Performance benchmarks:

Repository Size	Files	LOC	Runtime
Small	5	503	0.16s
Medium	34	3,029	0.24s
Large	77	10,025	0.27s
Very Large	351	30,063	0.55s

Unsafe patterns are refused instead of rewritten.

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Enterprise

Autonoma Community Edition focuses on deterministic local remediation for Python projects.

Planned enterprise capabilities include:

• policy enforcement
• CI/CD integration
• audit logs
• approval workflows
• multi-repository orchestration

Enterprise capabilities are under development.

If your team is interested in early evaluation or pilot deployments, feel free to reach out.

Contributing

Bug reports and edge cases are extremely valuable.

If Autonoma:

• fixes something incorrectly
• refuses a safe pattern
• misses a detectable secret

please open an issue with the code sample.

Pull requests are welcome.

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License

MIT License