The UiPath Security Auditor is the first purpose-built, production-grade security analysis platform for UiPath XAML automation workflows. It closes a critical and widely ignored gap in enterprise RPA security: the lack of automated, structured vulnerability detection in robotic process automation code.
This is not a linter. This is not a code formatter. This is a security auditing engine that treats your automation workflows with the same rigor applied to enterprise application code — because in 2024, they deserve nothing less.
RPA adoption has exploded across enterprises in banking, healthcare, insurance, and government. UiPath alone powers automation for over 10,000 organizations globally. These automations handle:
- Financial transactions — wire transfers, account reconciliations, invoice processing
- Healthcare records — patient data extraction, claims processing, EHR integration
- Identity and access — user provisioning, credential management, privileged access workflows
- Customer data — PII extraction, CRM updates, email processing
Yet the security review process for these workflows remains almost entirely manual, inconsistent, and often nonexistent.
The security community has invested decades in static analysis tools for Java, Python, C#, JavaScript. OWASP maintains threat models for web applications. NIST publishes secure coding standards. But XAML workflow analysis? Near zero tooling exists.
This is the gap the UiPath Security Auditor closes.
The emergence of UiPath's AI/LLM integration activities (UiPath.Langchain, UiPath.OpenAI, UiPath.MLServices) has introduced a category of risk that the RPA community is completely unprepared for: prompt injection attacks.
When an automation workflow:
- Scrapes data from a website
- Reads content from an email body
- Processes user-submitted forms
- Ingests data from external APIs
...and passes that data directly into an LLM activity without sanitization, an attacker can craft malicious content that hijacks the AI's behavior. The injected instructions can:
- Override system prompts to change the automation's behavior
- Exfiltrate sensitive data to attacker-controlled endpoints
- Cause the robot to approve fraudulent transactions
- Forge outputs that downstream systems trust
Traditional code review catches SQL injection. Nobody is looking for prompt injection in RPA workflows. We are.
This is the most widespread vulnerability in enterprise RPA code. Analysis of RPA audit engagements consistently reveals:
- API keys committed directly into
DefaultValueproperties of XAML variables - Database connection strings with embedded usernames and passwords
- OAuth tokens stored as hardcoded string literals
- AWS access keys (AKIA*) embedded in workflow arguments
- Private keys checked into version control alongside XAML files
The consequences are severe: any developer with repository access, any version control snapshot, any memory dump of a running Robot can expose these credentials. This scanner applies 19 distinct detection patterns covering API keys, JWT tokens, connection strings, OAuth secrets, AWS credentials, private keys, and more.
UiPath's rich activity library makes it trivially easy to:
- Make HTTP requests over unencrypted channels (
http://) - Disable SSL certificate validation (
AcceptAllCertificates=True) — a catastrophic MITM enabler - Pass plaintext passwords to authentication activities
- Write sensitive data to unencrypted local files
- Log credential values to Orchestrator audit logs
- Use deprecated TLS protocol versions
Each of these represents an exploitable attack surface. The auditor detects them all, maps them to CWE identifiers, and provides concrete, UiPath-specific remediation guidance.
The core scanner is a rule-based static analysis engine purpose-built for XAML structure:
XAML File → Line-by-Line Analysis → Pattern Matching → Finding Enrichment → Risk Scoring
13 security rules across 3 threat categories, each producing:
- Severity classification (Critical / High / Medium / Low / Info)
- CWE identifier mapping to the CVE/NVD ecosystem
- Code snippet with surrounding context (±2 lines)
- Activity type detection from XAML metadata
- Remediation guidance specific to UiPath's activity library
Risk scores are calculated using a weighted severity model:
| Severity | Weight |
|---|---|
| Critical | 10 pts |
| High | 7 pts |
| Medium | 4 pts |
| Low | 1 pt |
Score normalizes to 0-100 scale, with 50+ raw points mapping to maximum risk (100). This produces a consistent, comparable metric across audits.
Reports are generated entirely client-side using jsPDF, producing:
- Cover page — audit identity, date, risk score, risk level classification
- Executive summary — finding counts by severity and category
- Top remediations — prioritized action items
- Detailed findings table — all findings with severity badges
- Finding details — full descriptions, code snippets, and remediation steps per finding
Reports are audit-ready for security teams, compliance officers, and CISO briefings.
- Generic API key/secret/token/password assignments
- OpenAI API key format (
sk-*) - Google API key format (
AIza*) - AWS access key format (
AKIA*) - Bearer/Basic auth tokens in headers
- RSA and EC private key PEM headers
- Database/AMQP/Redis connection string URIs
- JWT token format (base64url.base64url.base64url)
- OAuth client_id/client_secret assignments
- UiPath XAML
DefaultValuewith base64-encoded secrets - Azure Key Vault connection strings with embedded service principal credentials (
RunAs=App;AppId=...;AppKey=...),*.vault.azure.netURIs co-located withClientSecret/AppKey, and Key Vault SAS tokens embedded in URLs (new in v1.1)
- UiPath.Langchain, UiPath.OpenAI, UiPath.CognitiveServices, UiPath.MLServices activities
- GenerateText, SendPrompt, ChatCompletion, InvokeChain activities
- Co-occurrence with external data inputs (GetRowItem, ReadRange, GetText, EmailBody)
- Dynamic system prompt construction patterns
- Unvalidated AI output used in downstream control flow
- HTTP (non-TLS) URLs for non-localhost endpoints
- AcceptAllCertificates/ValidateCertificate/IgnoreCertificateErrors flag states
- Plaintext password parameters in activity properties
- Sensitive keyword co-occurrence with file write and log activities
- HTTPS activities without explicit TLS version configuration
The findings produced by this tool align with NIST 800-53 controls:
- IA-5 (Authenticator Management) — hardcoded credentials
- SC-8 (Transmission Confidentiality) — unencrypted HTTP
- SC-17 (PKI Certificates) — certificate validation bypass
- SI-10 (Information Input Validation) — prompt injection
- A02:2021 Cryptographic Failures — hardcoded secrets, plaintext credentials
- A03:2021 Injection — prompt injection in LLM activities
- A07:2021 Identification and Authentication Failures — unsecured auth patterns
The convergence of three trends makes this tool critical:
- RPA at enterprise scale — robots now control systems that previously required privileged human access
- AI/LLM integration — UiPath's AI activities bring a new class of injection attacks to automation
- Compliance pressure — SOC 2 Type II, ISO 27001, and PCI DSS auditors are beginning to ask about RPA security controls
- Create an Audit — name your audit session for tracking
- Upload XAML Files — paste content or upload
.xamlfiles from your UiPath project - Run the Scan — the engine analyzes all files simultaneously
- Review Findings — filter by severity and category, inspect code snippets
- Download PDF Report — professional audit report ready for security review
- Git repository integration for direct project scanning
- UiPath Orchestrator API integration for automated workflow retrieval
- Custom rule authoring interface
- CI/CD pipeline plugin (GitHub Actions, Azure DevOps)
- SARIF output format for integration with GitHub Advanced Security
- Baseline comparison between audit sessions
- Multi-tenant organization support
Built for architects who know that security is not a feature — it is a foundation.