Skip to main content

🧠 Remenis: AI Memory Security Framework

Clean Context. Zero Bloat. Absolute Agent Containment.

Remenis is an open-source AI memory isolation framework designed to solve the AI agent memory poisoning problem. As autonomous agents execute multi-turn tasks independently, unvetted long-term memory accumulation and context injection can cause agents to go rogue, drift, or execute unauthorized tool calls without human oversight.

Remenis enforces strict runtime boundaries and memory hygiene to ensure agent state remains secure, fast, and untainted.


🚀 Key Architectural Updates

Remenis solves context drift and rogue agent behavior through 5 core pillars:

  1. 🛡️ OS Privilege Rings (RingContextGuard)
    • Multi-tiered hierarchical memory isolation (Ring-0 to Ring-2). Guarantees untrusted prompts and user context cannot corrupt, overwrite, or leak core system memory.
  2. 🔒 Security Guardrails
    • Real-time validation logic that intercepts and blocks prompt injection, context poisoning, and unauthorized memory modification before state updates persist.
  3. ⏳ Time-Decay Scoring
    • Algorithmic decay function that automatically deprioritizes stale or obsolete memory entries so the agent retrieves only high-fidelity, relevant context.
  4. ⚡ Fast Multi-Thread Writes
    • High-throughput concurrent execution pipeline optimized for parallel memory reads and writes in real-time agent workflows.
  5. 🧹 Auto-Deduping
    • Vector and semantic deduplication engine that removes redundant memory entries, delivering clean context with zero bloat.

🏗️ Architecture Overview

[ Incoming Prompt / Agent Context ]
                 │
                 ▼
 ┌──────────────────────────────┐
 │    Security Guardrails       │ (Real-Time Prompt Injection Defense)
 └───────────────┬──────────────┘
                 │
                 ▼
 ┌──────────────────────────────┐
 │    OS Privilege Rings        │ (RingContextGuard Isolation: Ring-2 -> Ring-0)
 └───────────────┬──────────────┘
                 │
                 ▼
 ┌──────────────────────────────┐
 │  Multi-Thread Memory Engine  │ (Auto-Deduping & Time-Decay Scoring)
 └───────────────┬──────────────┘
                 │
                 ▼
 [ Pure, Uncorrupted Context Output ]
🛠️ Quickstart & Integration
Install Remenis via PyPI or clone locally:

Installation
Bash
pip install remenis
Local Development Setup
Bash
# Clone repository
git clone [https://github.com/your-username/remenis.git](https://github.com/your-username/remenis.git)
cd remenis

# Set up virtual environment
python3 -m venv .venv
source .venv/bin/activate

# Install editable package
pip install -e .
Usage Example
Python
from remenis import MemoryEngine, RingContextGuard

# Initialize guard at isolation level 1
guard = RingContextGuard(ring_level=1)
memory = MemoryEngine(guard=guard)

# Process and store secure agent memory
clean_context = memory.process_input("User input payload")
🤝 Community & Benchmarks
We actively red-team Remenis against agentic vulnerabilities, memory poisoning, and context leakage patterns.

Automated Red-Teaming Suites: Run pytest tests/benchmarks/ to test RingContextGuard against known prompt injection vectors.

Contributing: Open an issue or pull request to submit new benchmark payloads or security guardrails.

📄 License
Distributed under the Apache 2.0 License. See LICENSE for details.

Metadata

Release files for remenis 0.1.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for remenis 0.1.3
File Size Uploaded Provenance Actions
remenis-0.1.3.tar.gz 14.4 kB Without provenance Details for remenis-0.1.3.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for remenis 0.1.3
File Interpreter ABI Platform Actions
remenis-0.1.3-py3-none-any.whl Python 3 none any Details for remenis-0.1.3-py3-none-any.whl

Total release size: 30.1 kB

Release files / remenis-0.1.3.tar.gz

Download URL remenis-0.1.3.tar.gz
Size 14.4 kB
Tags Source
SHA-256 checksum
How to use checksums
e07ce1a74994a54769bb359e43488a05a7e73917a7ba11d8e727998fe96f53a3
BLAKE2b-256 checksum
How to use checksums
27f2b3748b66e40a01f67217c94f23aa97700fb2f1949e3e783078f574460bca
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.14.4

Release files / remenis-0.1.3-py3-none-any.whl

Download URL remenis-0.1.3-py3-none-any.whl
Size 15.6 kB
Tags Python 3
SHA-256 checksum
How to use checksums
afd7051b88dfc8a10f773ab55e7ff92af2d6f5e3b8c306815b7f60425475864e
BLAKE2b-256 checksum
How to use checksums
08e73eac881dc1aa7e9ccd13916d27d3ad96e6f3046968e18524835a3cc4a186
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.14.4

Security for remenis 0.1.3

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page