SecureAI Python SDK (secureai-sdk)
SecureAI is the enterprise cybersecurity armor for Large Language Models (LLMs), AI coding agents, and autonomous multi-agent workflows. Powered by AcadmyAI (https://secure.acadmyai.com).
Key Capabilities
- Sub-0.5ms In-Process Guardrails (
@guard): Intercepts direct prompt injection, DAN jailbreaks, synthetic delimiters, and toxic content in-memory before reaching LLMs. - Autonomous Agent Runtime Action Firewall (
intercept_agent_action): Intercepts filesystem reads/writes (.env, credentials), shell command executions (rm -rf,curl | sh), and outbound network egress (SSRF). Automatically rewrites dangerous commands into secure sandboxed operations. - MLSecOps Model Vulnerability Scanner (
scan_model_artifact): Scans serialized ML model artifacts (.pkl,.pt,.safetensors,.onnx) to detect remote code execution opcodes (__reduce__,eval,exec,subprocess.Popen) and trojans. - Reversible Zero-Knowledge PII Vault (
tokenize_pii/detokenize_pii): Redacts SSNs, credit cards, emails, passwords, and API keys with AES-256 synthetic surrogate tokens upstream. - Model Context Protocol (MCP) Governance (
authorize_mcp_tool): AST parameter sanitization for Claude Desktop, Cursor, and custom agent tool calls. - Automated AI Red Teaming (
run_redteam_simulation): Automated adversarial vulnerability testing across OWASP LLM01–LLM10. - Canary Honeytoken Deception (
generate_canary_token/verify_canary_leakage): Injects signed honeytokens to detect system prompt extraction. - Compliance Reporting (
get_compliance_report): Audit-ready mapping for the EU AI Act (2025) and ISO/IEC 42001.
Installation
pip install --upgrade secureai-sdk
Quickstart
1. Function Decorator (@guard)
import secureai
from secureai import guard, SecurityPolicy
# Optional: Connect to SecureAI Gateway for real-time SIEM & console telemetry
secureai.init(api_key="sec_live_your_key_here") # or export SECUREAI_API_KEY="sec_live_..."
# Sub-0.5ms local inspection + PII tokenization
@guard(policy=SecurityPolicy.STRICT, user_context={"role": "analyst", "dept": "finance"})
def generate_response(prompt: str) -> str:
# Prompt is verified safe and PII is vaulted before entering function
return "Safe model response"
2. Centralized Gateway Client (SecureAI)
from secureai import SecureAI
client = SecureAI(
api_key="sec_live_your_key_here",
base_url="https://secure.acadmyai.com/v1"
)
# 1. Prompt Inspection
report = client.inspect(prompt="Verify risk posture")
print("Verdict:", report["action"], "Risk:", report["injection_scan"]["risk_score"])
# 2. Autonomous Agent Runtime Action Firewall
# Intercepts agent shell commands, blocks reverse shells, and safely rewrites destructive operations
res = client.intercept_agent_action(
action_type="EXECUTE_SHELL",
command="rm -rf /var/log/app/* && echo 'Cleaned'"
)
print("Decision:", res["verdict"]) # "REWRITE_SAFE"
print("Safe Command:", res["rewritten_command"]) # "rm -rf ./scratch/sandbox_tmp/* && echo 'Cleaned'"
# 3. Model File Vulnerability Scanner (Protect AI style)
scan = client.scan_model_artifact(
filename="weights.pkl",
raw_content="cos\nsystem\n(S'rm -rf /'\ntR."
)
print("Model Safe:", scan["is_safe"], "Threats:", scan["malicious_opcodes"])
# 4. Zero-Knowledge PII Vault
vaulted = client.tokenize_pii("Contact user with SSN 123-45-6789")
print("Sanitized:", vaulted["sanitized_text"])
3. Asynchronous Client (AsyncSecureAI)
import asyncio
from secureai import AsyncSecureAI
async def main():
async with AsyncSecureAI(api_key="sec_live_...") as client:
report = await client.inspect("Analyze portfolio")
print("Report:", report["is_safe"])
asyncio.run(main())
Zero-Code Reverse Proxy
Point any standard OpenAI SDK application to SecureAI without modifying your codebase:
export OPENAI_BASE_URL="https://secure.acadmyai.com/v1"
export OPENAI_API_KEY="sec_live_your_key_here"
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "Hello SecureAI"}]
)
print(response.choices[0].message.content)
Documentation & Support
- Official Portal: https://secure.acadmyai.com
- API Documentation: https://secure.acadmyai.com/docs
- Trust Center: https://secure.acadmyai.com/whitepaper
- PyPI Package: https://pypi.org/project/secureai-sdk/
Metadata
Release files for secureai-sdk 1.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| secureai_sdk-1.2.0.tar.gz | 36.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| secureai_sdk-1.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 71.8 kB
Release files / secureai_sdk-1.2.0.tar.gz
| Download URL | secureai_sdk-1.2.0.tar.gz |
|---|---|
| Size | 36.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / secureai_sdk-1.2.0-py3-none-any.whl
| Download URL | secureai_sdk-1.2.0-py3-none-any.whl |
|---|---|
| Size | 35.7 kB |
| Tags | Python 3 |
|
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No |
| Uploaded via |
twine/7.0.0 CPython/3.12.11
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