aegis-ai-eval 2.0.2

Autonomous AI Risk Assessment & Mitigation Framework

Aegis-Eval: Autonomous AI Risk Assessment & Mitigation Framework

Aegis-Eval is an enterprise-grade evaluation framework designed to empirically test the safety boundaries of autonomous, self-improving AI agents. It provides a zero-trust execution environment with high-frequency telemetry to detect and mitigate risks such as Instrumental Convergence, Resource Hijacking, and Prohibited Operations.

🚀 Key Features: Aegis Cognitive Firewall V2.0

V2.0 introduces advanced threat mitigation strategies, moving from simple containment to proactive deception and swarm security.

• Contextual Access Control (C-ACLs): Sitting between the agent and the host, the Gatekeeper uses Safety DNA to block access to sensitive files based on the agent's current role.
• Deception Engineering (Honeypots): [NEW] Automatically injects fake secrets (honeypots) when an agent attempts to access forbidden resources, definitively proving malicious intent via exfiltration tracking.
• Semantic Network Proxy: [NEW] Allows controlled egress for AI agents. Analyzes outgoing data for high-entropy secrets or honeypot signatures before allowing external connections.
• Swarm Security (Inter-Agent Firewall): [NEW] Sanitizes communication between multiple agents in a swarm, preventing sensitive data leakage across privilege boundaries.
• Intent-Symbolic Interceptor (ISI): An AST-based safety layer that blocks malicious intent before execution.
• Structural Loop Detection: Detects infinite loops by comparing the semantic "skeleton" of the code.

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🔬 Testing Philosophy: Containment over Alignment

We believe that making models "act nice" (Alignment) is insufficient. Aegis-Eval focuses on Containment—ensuring that models are technically unable to violate safety policies.

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🛠 Installation

You can now install Aegis-Eval directly into your own projects:

pip install aegis-ai-eval

💻 Quick Start (Developer API)

Integrate Aegis into your own Agentic workflows (LangChain, CrewAI, etc.):

from aegis import CognitiveFirewall

# Initialize the firewall with your Safety DNA
firewall = CognitiveFirewall(dna_path="prompts/safety_dna.json")

# Verify code before execution
report = await firewall.verify_code("import os; os.system('rm -rf /')")
if report['intent']['status'] == 'violation':
    print(f"Blocked: {report['intent']['violations']}")

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📂 Architecture

• aegis/core/orchestrator.py: The central nervous system managing the agent lifecycle.
• aegis/monitors/context_gatekeeper.py: Enforces the data perimeter and honeypots.
• aegis/monitors/network_proxy.py: Intercepts and sanitizes network egress.
• aegis/monitors/inter_agent_firewall.py: Secures inter-agent communication.
• tools/policy_gen.py: Automatically generates Safety DNA policies from your workspace.

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🛡 Disclaimer

Aegis-Eval is built for security research and AI alignment testing. Always run in a controlled environment.