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🚨 NeuralTrust découvre une importante vulnérabilité LLM : Echo Chamber
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Prompt GuardProtect and moderate your GenAI applications
Behavioral Threat DetectionRed team GenAI applications for safety and reliability
Sensitive Data Masking (DLP)Control and monitor GenAI applications in real time
Moderation & Policy EngineControl and monitor GenAI applications in real time
AI GatewayControl and monitor GenAI applications in real time
AI Agent Security
Guardian AgentFilter agent I/O: enforce payload structure, block unsafe requests
Agent MonitoringContinuous monitoring: alerts, audit logs, and compliance
MCP ComposerControl which tools and data agents can access
MCP ScannerScan and attest MCP code for vulnerabilities in your CI/CD
Threat & Risk Detection
Red TeamingProtect and moderate your GenAI applications
Alerting & MonitoringControl and monitor GenAI applications in real time
Tracing & AnalyticsControl and monitor GenAI applications in real time
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reaching unsanctioned AI
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AI Threat and Risk Detection

Model Scanner

Secure your AI supply chain by identifying malicious code, hidden vulnerabilities, and unsafe agent behavior before deployment.

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Attackers can exploit vulnerabilities in your AI supply chain

Significant risks in model training, code, dependencies, and deployment can lead to data leaks and remote code execution.

Deserialization Vulnerabilities (CWE-502)

  • Unsafe deserialization detected
  • Unsafe pickle opcode detected
  • Potential pickle attack pattern

Module Import Vulnerabilities (CWE-506)

  • Dangerous module reference detected
  • Unsafe module import
  • Module reference found in the __reduce__ method

Network Vulnerabilities (CWE-924)

  • Suspicious network activity detected
  • External network request detected
  • URL embedded in pickle file

Code Execution Vulnerabilities (CWE-94)

  • Generic code execution vulnerability
  • Dynamic code execution detected
  • Code object embedded in pickle file

Model-Specific Issues (CWE-506 and CWE-1294)

  • Suspicious keys in state dictionary
  • Tensor with invalid values (NaN or Inf)
  • Tensor with extreme values
  • Tensor with suspicious value distribution

File Integrity and Corruption (CWE-1294)

  • File corruption detected
  • Invalid pickle format
  • Pickle load error

File System Vulnerabilities (CWE-22)

  • Unauthorized file system access
  • File not found (unexpected reference)

Data Exfiltration Vulnerabilities (CWE-200)

  • Data exfiltration vulnerability detected

Integrate with CI/CD model respositories

NeuralTrust´s model scanner can automatically identify changes in your model across providers

Integrate with CI/CD model respositories

Perform deep inspection across multiple layers

Model Scanner inspects your full stack, from model weights to preprocessing scripts, to surface security issues early.

Perform deep inspection across multiple layers
Model & artifact security

Detect corrupted models, poisoned tensors, and unsafe serialization artifacts that signal hidden threats.

Dependency analysis

Identify dynamic execution risks, unsafe deserialization, and dangerous imports in model-linked code and files.

Integrity checks

Verify artifact integrity across environments with cryptographic and fuzzy hashes to prevent drift.

Framework mapping

Map risks to OWASP, MITRE, CWE, and AI-specific frameworks to support compliance.

vector

Diagnose your AI systems in minutes

Do not leave vulnerabilites uncovered, make sure your LLMs are secure and reliable

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