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Description
Silmaril is an innovative defense mechanism against prompt injection that autonomously heals itself, aiming to safeguard AI systems from sophisticated, multi-layered threats that conventional barriers cannot mitigate. Unlike traditional methods that merely filter inputs, it envelops inference calls, assessing whether the sequence of actions is steering towards a detrimental result. By employing a multihead classifier, it evaluates user intentions, application contexts, and execution states simultaneously, which allows it to identify indirect injections, multi-turn attack sequences, context manipulation, and tool exploitation before any harm can occur. To enhance its protective capabilities, Silmaril incorporates autonomous threat-hunting agents that explore systems, identify weaknesses, and produce synthetic training data based on actual attack incidents. These findings facilitate automatic model retraining, allowing for the deployment of updated defenses in less than an hour, while simultaneously disseminating anonymized protective measures across all instances. Moreover, this proactive approach ensures that the system remains resilient against emerging threats, adapting continuously to the evolving landscape of cybersecurity challenges.
Description
Workplace use of AI tools such as ChatGPT, Copilot, Claude, Perplexity and DeepSeek has surged, often without oversight from IT departments. More than 92% of employees now use generative AI at work, exposing financial data, API keys, passwords, source code and personal records. Traditional Data Loss Prevention (DLP) solutions and proxies were not built for this new threat. Enter ZeusLock, a DLP solution designed specifically for the AI era. It analyzes prompts, files and images in real time and detects, anonymizes or blocks sensitive data before it reaches any AI service. Deployment takes about two minutes through a browser extension and an endpoint agent for Windows, macOS and Linux, protecting web apps, desktop apps, IDEs, terminals and AI agents, including their connections through the Model Context Protocol (MCP). Each data type is set to Off, Alert or Block per policy; Alert mode can anonymize values while preserving their format, and every incident is logged in masked form for auditing. ZeusLock also stops prompt injection and jailbreak attacks, and its Shadow AI Discovery maps the AI tools employees actually use, with risk scores and approval status. Detection relies on a dedicated multimodal language model backed by deterministic rules, hosted in Europe, or fully on-premise with the Sovereign Edition, with no US cloud dependency. This approach lets organizations embrace AI tools with confidence while keeping their data secure.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Agent Development Kit (ADK)
Yes
Claude
Yes
Claude Code
Yes
Claude Duet
Yes
Claude for Legal
Yes
CrewAI
Yes
LangChain
Yes
Model Context Protocol (MCP)
No
OpenAI
Yes
OpenClaw
Yes
Integrations
Agent Development Kit (ADK)
No
Claude
No
Claude Code
No
Claude Duet
No
Claude for Legal
No
CrewAI
No
LangChain
No
Model Context Protocol (MCP)
Yes
OpenAI
No
OpenClaw
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Simaril
Country
United States
Website
www.silmaril.dev/
Vendor Details
Company Name
ZeusLock
Founded
2025
Country
France
Website
zeuslock.ai