Welcome
AI-powered security
AppScan on Cloud recognizes the increasing role of artificial intelligence in development protocols. Just as AI can speed and strengthen the application development process, so can AI be used to ensure those applications are secure and ready for market.
AI innovations in AppScan on Cloud
Agentic AI for Business Logic Vulnerability Detection in SAST

Getting started
Welcome to the documentation for HCL AppScan on Cloud, where you can find information about how to install, maintain, and use this service.
Navigation
This section describes navigating AppScan on Cloud, including items on the side main menu and top navigation bars, with links to more detailed information.
Management
Define users, roles, groups, applications, policies, and configure DevOps integrations.
Dynamic analysis
AppScan on Cloud performs security scans for web-applications for production, staging and development environments. For development environments it is aided by Private Site Scanning technology to scan applications not accessible to the open Internet.
Interactive monitoring
Using an agent installed on your application, ASoC identifies security vulnerabilities in your application during runtime by monitoring all interactions, both legitimate and malicious. The process is "passive," in the sense that IAST does not send its own tests, and can therefore run indefinitely.
Software Composition Analysis
Use Software Composition Analysis (SCA) to scan for security vulnerabilities in open source and third-party packages used by your code.
Static analysis
Use static analysis (SAST) to scan for security vulnerabilities in web and desktop applications. Static analysis includes Intelligent Finding Analytics (IFA) and Intelligent Code Analytics (ICA).
AI-powered security
AppScan on Cloud recognizes the increasing role of artificial intelligence in development protocols. Just as AI can speed and strengthen the application development process, so can AI be used to ensure those applications are secure and ready for market.
- AI innovations in AppScan on Cloud
  - HCL AppScan RapidFix integration
    HCL AppScan RapidFix is an AI-driven solution that automates the triage and remediation process for application security vulnerabilities. HCL AppScan RapidFix applies to SAST results.
  - AppScan on Cloud AI assistant
    The AI assistant is an integrated intelligence layer that works within the AppScan on Cloud environment. It provides security insights, automates issue triage, and offers remediation guidance.
  - AppScan Model Context Protocol (MCP) server
    The AppScan MCP server integrates HCL AppScan on Cloud directly with AI-powered development environments and agents. By implementing the Model Context Protocol (MCP), this server allows LLMs (such as Claude or models running in VS Code) to securely access your security data—including SAST, DAST, SCA, and IAST results—to help you triage issues, analyze findings, and automate workflows using natural language.
  - Intelligent Findings Analytics (IFA) and Intelligent Code Analysis (ICA) for SAST
  - Agentic AI for Business Logic Vulnerability Detection in SAST
  - Intelligent Finding Analytics (IFA) and DAST
    Intelligent Finding Analytics (IFA) uses artificial intelligence (AI) and machine learning (ML) to analyze data, discover patterns, and make predictions, ultimately transforming data into actionable insights. IFA goes beyond regular data analysis by using advanced methods to find deeper meanings and make smart decisions.
- AI security in AppScan on Cloud
  In AppScan on Cloud traditional scans can cover conventional vulnerabilities within AI architecture.
Results
The Scans and Sessions page lists the scans under the categories DAST, SAST, SCA, and IAST, where you can view your scan results, including scan statistics. To view, rescan, or download reports, select a scan.The Scans and Sessions page lists scans under the categories where you can view your scan results, including scan statistics. To view, rescan, or download reports, select a scan.
Troubleshooting
If you experience problems with this service, you can perform these troubleshooting tasks to determine the corrective action to take.
FAQ & Reference
Frequently asked questions, information about integrating ASoC into the product lifecycle (SDLC), and ASoC API documentation.

Agentic AI for Business Logic Vulnerability Detection in SAST

Business logic vulnerabilities arise when an application’s workflows, authorization rules, state transitions, or business constraints can be manipulated to produce unintended outcomes. Examples include bypassing approval steps, exceeding transaction limits, changing workflow sequences, or performing restricted operations. Because these weaknesses depend on application-specific intent and context, traditional SAST tools, which rely primarily on predefined rules and data-flow patterns, struggle to detect them.

AppScan’s Agentic BL scanner enhances SAST by using a specialized security agent with controlled, programmatic access to the application’s source code. The agent explores relevant code paths, identifies business entities and workflows, reasons across functions and components, and evaluates whether application behavior conflicts with inferred security and business constraints.

Agentic analysis can help identify issues such as:

Missing or inconsistent authorization checks
Bypassed approval or validation steps
Improper workflow and state transitions
Abuse of privileged business operations
Inconsistent enforcement across APIs or application layers
Trust-boundary violations and unsafe assumptions

Potential findings are validated against supporting code paths and presented alongside conventional SAST results through a unified experience. Each finding can include contextual evidence, the affected workflow, risk details, and remediation guidance, helping security and development teams understand and address complex vulnerabilities more efficiently.

By combining agentic reasoning with established static analysis, AppSec platforms can expand coverage beyond syntax-level and data-flow vulnerabilities to identify application-specific logic flaws earlier in the SDLC, without requiring the application to be deployed or running.