Six security engines. One platform.
Scan every repo for vulnerabilities, secrets, dependency risks, and AI attack-surface exposure. SAST findings are triaged by AI that reasons about real exploitability.
SAST Scanning
Static Application Security Testing
Multi-engine static analysis that scans your source code for security vulnerabilities across a broad range of languages (Python, JS/TS, Java, Go, Ruby, PHP, C#, Kotlin, Scala, and more). AI-powered triage reduces false positives using exploitation-focused reasoning.
- OWASP Top 10 + CWE coverage
- Broad language coverage (Python, JS/TS, Java, Go, Ruby, PHP, C#, and more)
- AI triage with configured model verification
- Triage carry-forward across scans
- Custom rule support
SCA & Dependencies
Software Composition Analysis
Comprehensive dependency scanning with regularly updated vulnerability data. EPSS scoring prioritizes what attackers actually exploit, not just CVSS severity.
- SBOM generation (CycloneDX + SPDX)
- EPSS + KEV exploitation scoring
- License compliance checking
- VEX document support
- Dependency graph visualization
- Transitive vulnerability tracking
Secret Detection
Credential & API Key Scanning
Detect hardcoded API keys, tokens, passwords, and credentials across configured repositories and available git history before they reach production.
- Common secret patterns
- Git history scanning
- Secret exposure alerts
- Entropy-based detection
- Custom regex patterns
IaC Security
Infrastructure as Code Scanning
Scan Terraform, CloudFormation, Kubernetes manifests, and Dockerfiles for security misconfigurations before they reach your cloud infrastructure.
- Terraform + CloudFormation
- Kubernetes manifest scanning
- Dockerfile best practices
- CIS Benchmark compliance
- Multi-cloud support (AWS, GCP, Azure)
AI PR Review
Automated Code Review
Configured pull requests are reviewed with a multi-category weighted rubric. Security, secrets, data handling, code quality, and architecture are scored independently with impact blast-radius diagrams.
- Security + Secrets + Data Handling + Code Quality + Architecture scoring
- Impact blast radius diagrams
- Inline fix suggestions in PR comments
- Branch-level quality gates
- Team learning from review history
AI Attack Surface Management
AI Integration Inventory & Risk Patterns
Inventory every AI SDK, model, and API endpoint your code actually uses - across providers and orchestration frameworks - then flag risky patterns in those integrations so nothing ships unreviewed.
- Detects AI SDKs & providers (OpenAI, Anthropic, Gemini, Bedrock, and more)
- Inventories models and AI API endpoints in use
- Flags PII passed into prompts
- Flags prompt-injection-prone input handling
- Flags unpinned model versions and missing error handling around LLM calls
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