norviq
★ 26
vs
WonderSuite-Ai-Bug-Bounty
★ 51
norviq vs WonderSuite-Ai-Bug-Bounty
norviq: Norviq is a policy enforcement point that intercepts and evaluates every LLM agent tool call against OPA/Rego policies on Kubernetes. It prevents potential risks like prompt injection or reasoning errors by ensuring tools only run if explicitly allowed by policy, enhancing AI safety and auditability.; WonderSuite-Ai-Bug-Bounty: WonderSuite is a desktop-native offensive security engine combining Burp Suite-class tooling with autonomous AI agent capabilities for web application security testing. It provides a fully integrated environment for network reconnaissance, exploit development, and vulnerability scanning, all orchestrated through an MCP-compatible AI interface.
01
TL;DR
norviqSecurity & Safety · ★ 26
Preventing LLM agents from executing unauthorized or dangerous tool calls, such as `execute_sql` or `send_email` without explicit policy approval.
WonderSuite-Ai-Bug-BountySecurity & Safety · ★ 51
AI-driven Vulnerability Research: Autonomously discover and analyze security vulnerabilities in web applications using AI agents.
02
Side-by-Side Comparison
Field
norviqWonderSuite-Ai-Bug-BountyCategory
Security & Safety
Security & Safety
Stars
★ 26
★ 51
License
Apache-2.0
MIT
Install Command
kubectl create namespace norviq && kubectl create namespace default && helm install norviq oci://ghcr.io/norviq-dev/charts/norviq --version 0.2.5 -n norviq --set 'policyQuotaNamespaces={default}' --set config.dbSslMode=disable
git clone https://github.com/sfr-development/WonderSuite-Ai-Bug-Bounty.git && cd WonderSuite-Ai-Bug-Bounty && npm install
Updated
3w ago
4d ago
Open Source
Yes
Yes
Tags
LLM Agents, Policy Enforcement, Kubernetes
AI Security, Offensive Security, Vulnerability Research
03
Features
norviq01Policy enforcement using OPA/Rego for sub-second, fail-closed evaluation of agent tool calls.
02Kubernetes-native deployment with custom resource definitions (CRDs), a mutating webhook, and Helm chart support.
03Supports workload identity using SPIFFE/SPIRE SVIDs for granular, per-agent-class and per-namespace policy scoping.
04Provides a Console UI for policy catalog/editor, attack/asset graphs, agent trust management, and audit stream.
05Includes a red-team suite with built-in adversarial tests to validate policy effectiveness against attacks like prompt injection or SQLi.
WonderSuite-Ai-Bug-Bounty01Intercepting Proxy: Full man-in-the-middle proxy with TLS interception, dynamic CA, and Chrome 137 JA3/JA4 + HTTP/2 fingerprint impersonation to bypass bot detection.
02WonderBrowser: A bundled, version-locked Chrome-for-Testing (148) with stealth extension and human-native agent input to avoid bot detection.
03MCP Server & 90+ Tools: Native Model Context Protocol server enabling AI agents to autonomously conduct security research using 90+ purpose-built security tools.
04Code Audit: A passive source-level audit module within the Sitemap, analyzing captured assets for secrets, tokens, API endpoints, and links with 60+ regex patterns.
05Port Scanner: An in-process, adaptive port scanner with three engines (TCP Connect, TCP SYN, UDP) and Nmap-service-probes integration for service detection.
04
Use Cases
norviq↳Preventing LLM agents from executing unauthorized or dangerous tool calls, such as `execute_sql` or `send_email` without explicit policy approval.
↳Ensuring compliance by enforcing policy-driven gates on agent tool interactions and providing comprehensive audit logs for all decisions.
↳Implementing fine-grained security policies for different agent classes and namespaces within a Kubernetes environment.
↳Detecting and blocking prompt injection or reasoning errors that could lead to malicious tool execution or data exfiltration.
WonderSuite-Ai-Bug-Bounty↳AI-driven Vulnerability Research: Autonomously discover and analyze security vulnerabilities in web applications using AI agents.
↳Web Application Penetration Testing: Conduct comprehensive security assessments of web applications, including proxying, scanning, and fuzzing.
↳Network Reconnaissance: Perform detailed network mapping and service identification using advanced port scanning and OSINT tools.
↳Exploit Development: Facilitate the creation and testing of exploits with integrated tooling for request manipulation, fuzzing, and out-of-band interaction.
↳Bot Detection Bypass Research: Investigate and bypass advanced bot detection mechanisms (e.g., Cloudflare, Akamai) using its stealthy browser and TLS impersonation features.
FAQ
FAQ
What is the difference between norviq and WonderSuite-Ai-Bug-Bounty?
Both norviq and WonderSuite-Ai-Bug-Bounty are in the Security & Safety category. norviq has 26 stars, while WonderSuite-Ai-Bug-Bounty has 51 stars.
Which is better, norviq or WonderSuite-Ai-Bug-Bounty?
The best choice depends on your use case. Choose norviq if Preventing LLM agents from executing unauthorized or dangerous tool calls, such as `execute_sql` or `send_email` without explicit policy approval., and WonderSuite-Ai-Bug-Bounty if AI-driven Vulnerability Research: Autonomously discover and analyze security vulnerabilities in web applications using AI agents..
Is norviq free or open source?
Yes, norviq is open source on GitHub (Apache-2.0).
Is WonderSuite-Ai-Bug-Bounty free or open source?
Yes, WonderSuite-Ai-Bug-Bounty is open source on GitHub (MIT).
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