BerriAI/litellm
Mar 2026 – Mar 2026
1 Month active
Languages Used
MarkdownPythonTypeScript
Technical Skills
API IntegrationBackend DevelopmentData Loss Prevention (DLP)GuardrailsLLM SecurityPalo Alto Networks Prisma AIRS
Jason Roberts
PROFILE
Jason Roberts
During March 2026, J. Roberts developed the PANW Prisma AIRS guardrail integration for the BerriAI/litellm repository, focusing on enhancing AI application security. They extended the apply_guardrail function to support the Prisma AIRS provider, introducing configurable options, per-request overrides, and robust error handling with both fail-open and fail-closed modes. Their work incorporated advanced security features such as prompt injection detection, data loss prevention, and content masking, laying the groundwork for comprehensive LLM security. The implementation leveraged Python and TypeScript for backend development and API integration, demonstrating depth in secure system design and attention to configurable, resilient error management.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
6,042
Activity Months1
Your Network
2781 peopleSame Organization
@users.noreply.github.com2060
Work History
March 2026
1 Commits • 1 Features
Mar 1, 2026Month 2026-03: Delivered PANW Prisma AIRS Guardrail integration for BerriAI/litellm. Extended apply_guardrail to support Prisma AIRS provider with configurable options, per-request overrides, and robust error handling with fail-open/fail-closed modes. Implemented guardrails features such as prompt injection detection, data loss prevention, and content masking to strengthen security posture across AI applications.
1 Commits • 1 Features
Mar 1, 2026Month 2026-03: Delivered PANW Prisma AIRS Guardrail integration for BerriAI/litellm. Extended apply_guardrail to support Prisma AIRS provider with configurable options, per-request overrides, and robust error handling with fail-open/fail-closed modes. Implemented guardrails features such as prompt injection detection, data loss prevention, and content masking to strengthen security posture across AI applications.
March 2026
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance80.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
MarkdownPythonTypeScript
Technical Skills
API IntegrationBackend DevelopmentData Loss Prevention (DLP)GuardrailsLLM SecurityPalo Alto Networks Prisma AIRSPrompt Injection DetectionSecurity
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