Unified LLM Security and Governance Gateway with Arabic and English Prompt-Injection Protection

The end client is a Saudi Arabia-based technology company operating in the AI security and governance sector. The organisation supports enterprises seeking to deploy large language models securely within regulated environments.

The client required a unified security gateway capable of protecting enterprise AI applications against emerging threats while supporting bilingual operations and regional governance requirements.

The end client’s identity is withheld due to contractual confidentiality and NDA obligations.

• Prompt-Injection Protection

  A real-time protection layer was implemented to inspect prompts before they reached the connected language model.

  Key capabilities included

  • Identification of prompt-injection attempts
  • Blocking of malicious or manipulated prompts
  • Input inspection using LLM Guard and complementary open-source tools
  • Configurable protection policies for different AI applications
  • Centralised visibility of detected threats

  Data Exfiltration Prevention

  Controls were introduced to reduce the risk of confidential or restricted information being exposed through AI interactions.

  The solution provided

  • Inspection of model inputs and outputs
  • Detection of potentially sensitive information
  • Blocking and flagging of high-risk interactions
  • Automated logging of data-protection events
  • Configurable rules based on organisational security requirements

  Bilingual Content Filtering

  A dedicated bilingual filtering layer was developed to analyse Arabic and English AI interactions.

  This enabled

  • Arabic and English input inspection
  • Arabic and English output inspection
  • Detection of unsafe or restricted content
  • Consistent application of security policies across both languages
  • Improved suitability for organisations operating across Saudi Arabia and the wider GCC

  Red-Team Simulation and Risk Scoring

  A controlled testing module was implemented to evaluate how AI applications responded to adversarial prompts and simulated attacks.

  Capabilities included

  • Red-team attack simulation
  • Testing against known AI security threats
  • Localised risk scoring
  • Centralised risk dashboards
  • Visibility of identified vulnerabilities
  • Support for remediation and security-policy improvement

  Compliance Logging and Framework Mapping

  The gateway provided governance capabilities to support oversight and audit readiness.

  These included

  • Automated logging of AI interactions and security events
  • Traceable records of blocked and flagged requests
  • Risk classification and reporting
  • Mapping of identified risks to relevant OWASP guidance
  • Governance information supporting NCA ECC and PDPL alignment

The project was delivered through SilwaTech’s partner ecosystem under a partner-led implementation model.

The technical architecture, development, integration, testing, and implementation of the solution were performed by an experienced SilwaTech partner company. SilwaTech contributed through engagement alignment, partner collaboration, and the coordination of relevant AI security capabilities.

The delivery team included specialists in

• AI and LLM security
• Backend and gateway engineering
• Arabic and English language processing
• Security-tool integration
• Dashboard and reporting development
• Quality assurance and security testing

The solution was developed iteratively, beginning with core prompt-injection and data-protection controls before expanding into bilingual filtering, red-team simulation, risk scoring and compliance reporting.

The identities of the end client and implementation partner remain confidential. SilwaTech does not represent itself as the direct contracting party or sole technical implementer for this engagement.