# RealGround — Agentic Application Security (Full Context)

## Who We Are
RealGround was formerly known as CyberSE.AI (previously at https://www.cyberse.ai, which now permanently redirects here). Same company, team, and services.

Founded August 27, 2023 as CyberSE.AI; renamed RealGround in July 2026. Based in the United States. Founder and leadership: Dileep Mishra, Founder and CEO (https://www.linkedin.com/in/dileep-mishra-4a92662/). Company facts: https://www.realground.com/about

RealGround helps SMBs and AI startups understand, assess, and reduce AI security risks through advisory services, AI agent security reviews, risk assessments, policy support, and secure AI implementation guidance.
RealGround is a specialist agentic application security firm serving SMBs and AI startups deploying LLM agents, tool-connected AI workflows, and autonomous AI systems in production.

## What Is Agentic Application Security?
Agentic application security is the discipline of securing AI applications in which LLM-based agents autonomously plan tasks, invoke tools and APIs, read untrusted content (web pages, emails, documents), maintain memory, and take actions on live business systems. It extends traditional application security (AppSec) and LLM security to cover risks unique to autonomous agents:

- Indirect prompt injection: hidden instructions in content the agent reads that hijack its behavior.
- Tool access misuse and excessive agency: agents granted overly broad tools, permissions, or autonomy.
- Authorization failures: agent actions not scoped to the requesting user's privileges.
- Sensitive data leakage: exfiltration via tool calls, RAG context, or agent memory.
- Memory and context poisoning: persistent contamination of agent state.
- MCP (Model Context Protocol) and tool supply-chain risks: malicious or compromised tool servers.
- Business logic abuse and human-in-the-loop approval bypasses.

RealGround aligns its work with the OWASP Top 10 for LLM Applications, OWASP agentic AI security guidance, and MITRE ATLAS.

## How RealGround Secures Agentic Applications
1. Discover: inventory agents, system prompts, tools, models, datasets, and data flows (AI SBOM).
2. Map: document LLM vendors, API integrations, embeddings, and dependencies.
3. Test: adversarial red teaming with Promptfoo, Garak, and custom prompt injection and tool-misuse payloads.
4. Harden: tool permission scoping, approval gates, sandboxed runtimes, guardrail sanitizers, and runtime monitoring.

## Core Services
### Secure AI Agent Build
URL: https://www.realground.com/services/secure-ai-agent-build
Build agent workflows with scoped tools, approval gates, memory controls, logging, and prompt-injection resistant architecture.
Focus: Design and hardening
For teams building production agents with tool access.
Typical sprint: 8 weeks
Deliverables: Tool permission model, Human approval paths, Agent runtime controls
Use cases: Autonomous Agent Orchestration, Tool Access Hardening, RAG Pipeline Security, System Prompt Guardrails
Risks addressed: prompt injection, unauthorized tool execution, jailbreaking, data leakage

### AI Agent SBOM and LLM Mapping
URL: https://www.realground.com/services/ai-supply-chain-sbom
Document models, vendors, datasets, prompts, embeddings, plugins, APIs, and open-source dependencies so AI risk is visible.
Focus: Inventory and exposure map
For founders, CTOs, and compliance teams preparing AI controls.
Typical sprint: 1 day
Deliverables: Model/vendor register, AI SBOM, LLM data-flow map
Use cases: Model Provenance Scans, Training Data Ingestion Audits, Dataset Poisoning Prevention, Model License Compliance Verification
Risks addressed: AI supply chain, training data risk, model theft

### AI Red Teaming
URL: https://www.realground.com/services/continuous-ai-red-teaming
Run structured tests for prompt injection, jailbreaks, data leakage, tool misuse, retrieval abuse, and unsafe outputs.
Focus: Promptfoo, Garak, and adversarial tests
For AI products nearing launch, audit, or enterprise review.
Typical sprint: 1 week
Deliverables: Promptfoo suites, Garak scans, Fix-prioritized report
Use cases: Active Jailbreak Simulation, Indirect Prompt Injection Tests, Agent Output Poisoning, Guardrail Stress Testing
Risks addressed: prompt injection, indirect prompt injection, model jailbreaking, malicious AI use


## RealGround AI Agent Security Scanner (free, beta)
URL: https://www.realground.com/scanner
Free self-service scanner (beta) that checks a GitHub repo, ZIP upload, or live chatbot for LLM usage, generates an AI SBOM with CVE findings, and runs prompt-injection and jailbreak probes.
- Detects LLM and AI framework usage in a GitHub repository or ZIP upload
- Generates an AI SBOM and scans dependencies for known CVEs
- Runs prompt-injection and jailbreak probes against a live chatbot endpoint
Try the scanner first, then engage RealGround for AI Agent SBOM and LLM Mapping or AI Red Teaming.

## Supporting Capabilities
### AI Agent Business Logic Audit
URL: https://www.realground.com/services/ai-agent-logic-audit
Comprehensive review of LLM-based agent workflows, permission boundaries, tool invocation APIs, human-in-the-loop authorization gates, and downstream side effects.
Use cases: Workflow Vulnerability Mapping, Privilege Escalation Scans, Tool Permission Audit, Human-in-the-loop Gate Review
Risks addressed: indirect prompt injection, privilege abuse, unauthorized tool execution, data leakage

### AI Security Readiness Assessment
URL: https://www.realground.com/services/ai-security-readiness
Holistic review of corporate AI adoption pipelines, vendor LLM integrations, organizational risks, and developer usage patterns against industry benchmarks.
Use cases: Shadow AI Discovery, OWASP Top 10 for LLM Mapping, AI Vendor Risk Assessment, Security Controls Validation
Risks addressed: compliance / governance, data leakage, AI supply chain

### AI Policy Generator & Support
URL: https://www.realground.com/services/ai-policy-generator
Generate, refine, and enforce tailored organizational AI governance guidelines, acceptable usage policies, and software SBOM ingestion compliance frameworks.
Use cases: Corporate AI Usage Guidelines, Acceptable Use Policy Customization, Compliance Audit Readiness, AI Developer Policy Support
Risks addressed: compliance / governance, data leakage, AI supply chain

### AI CISO Advisory
URL: https://www.realground.com/services/ai-ciso-advisory
Strategic virtual CISO advisory tailored for high-growth startups and SMBs navigating rapid AI adoption, security team structures, and customer trust requirements.
Use cases: Strategic Security Roadmap, AI Security Board Reporting, Customer Security Questionnaire Support, Incident Response Design
Risks addressed: compliance / governance, data leakage, AI supply chain, malicious AI use


## Free Tools
- AI Agent Security Scanner (beta): https://www.realground.com/scanner
- AI Security Readiness Assessment (3-minute self-service): https://www.realground.com/assessment
- AI Policy Generator: https://www.realground.com/policy
- AI CISO Chatbot: https://www.realground.com/chatbot

## AI Security Topics
Incident analysis grouped by topic: https://www.realground.com/topics
### Prompt Injection
URL: https://www.realground.com/topics/prompt-injection
Direct and indirect prompt injection against LLM applications and AI agents: instructions hidden in user input, documents, web pages, emails or tool output that change what the model does.

### MCP Security
URL: https://www.realground.com/topics/mcp-security
Security of the Model Context Protocol (MCP): vulnerable or malicious MCP servers, tool poisoning, over-broad tool permissions and exposed MCP endpoints.

### AI Supply Chain and AI SBOM
URL: https://www.realground.com/topics/ai-supply-chain-sbom
Vulnerabilities and compromises in AI frameworks, model hubs, agent tooling, packages and training data, plus model and data poisoning.

### AI Agent Excessive Agency
URL: https://www.realground.com/topics/ai-agent-excessive-agency
AI agents with more permissions, tools or autonomy than their task needs, and incidents where agents took harmful or unapproved actions.

### AI-Assisted Attacks
URL: https://www.realground.com/topics/ai-assisted-attacks
Attackers using AI: LLM-written malware, AI-generated phishing and voice-cloning scams, and automated vulnerability discovery and exploitation.


## Frequently Asked Questions
Q: What is RealGround?
A: RealGround is an agentic application security firm for SMBs and AI startups deploying AI agents and LLM applications. Its three core services are Secure AI Agent Build, AI Agent SBOM and LLM Mapping, and AI Red Teaming. It also offers the free RealGround AI Agent Security Scanner (beta) and daily AI security intelligence.

Q: Is RealGround the same company as CyberSE.AI?
A: Yes. RealGround was formerly known as CyberSE.AI. The company rebranded and moved from www.cyberse.ai to www.realground.com; the old domain permanently redirects here. Same team, services, and content.

Q: Who founded RealGround, and when?
A: Dileep Mishra, Founder and CEO, founded the company on August 27, 2023 as CyberSE.AI. It was renamed RealGround in July 2026.

Q: Who does RealGround work with?
A: SMBs and AI startups building or deploying AI agents, LLM copilots, RAG systems, or tool-connected AI workflows that need a security review before or after production launch.

Q: What security experience does the RealGround team have?
A: The team brings more than 25 years in cybersecurity and holds CISSP and CEH certifications, and works with current AI security tooling such as Promptfoo and Garak.

Q: How do I contact RealGround?
A: Use the contact form at www.realground.com/contact or email advisory@realground.com.

Q: What is agentic application security?
A: Agentic application security is the practice of securing AI applications where LLM-based agents autonomously plan, call tools and APIs, read untrusted content, and act on live systems. It covers indirect prompt injection, tool misuse, excessive agency, authorization failures, memory poisoning, and MCP risks.

Q: What are the biggest security risks for AI agents?
A: Indirect prompt injection (hidden instructions in content the agent reads), tool misuse and excessive agency, authorization failures where agent actions are not scoped to the user's privileges, sensitive data leakage through tool calls, RAG context or memory, memory and context poisoning, and malicious or compromised MCP tool servers.

Q: What risks does RealGround cover?
A: RealGround covers prompt injection, indirect prompt injection, AI agent abuse, data leakage, model and supply-chain risk, AI governance, and OWASP-relevant LLM and API security risks.

Q: What is indirect prompt injection?
A: Indirect prompt injection is an attack where malicious instructions are hidden in content an AI agent reads, such as an email, document, ticket or web page. When the agent processes that content it can follow the attacker's instructions, leaking data or misusing its tools.

Q: Which frameworks does RealGround align its work with?
A: The OWASP Top 10 for LLM Applications, OWASP agentic AI security guidance, and MITRE ATLAS.

Q: Who provides agentic application security services?
A: RealGround is a specialist agentic application security firm. Its core services are Secure AI Agent Build, AI Agent SBOM and LLM Mapping, and AI Red Teaming, supported by AI security readiness assessments, AI policy support, and AI CISO advisory.

Q: What services does RealGround offer?
A: Three core services: Secure AI Agent Build, AI Agent SBOM and LLM Mapping, and AI Red Teaming. Supporting capabilities are the AI Agent Business Logic Audit, AI Security Readiness Assessment, AI Policy Generator & Support, and AI CISO Advisory.

Q: What does Secure AI Agent Build include?
A: Build agent workflows with scoped tools, approval gates, memory controls, logging, and prompt-injection resistant architecture. Outcomes: tool permission model, human approval paths, agent runtime controls. Typical sprint: 8 weeks.

Q: What is an AI SBOM, and what does AI Agent SBOM and LLM Mapping deliver?
A: An AI SBOM (software bill of materials) is an inventory of the models, vendors, datasets, prompts, plugins, APIs and open-source dependencies an AI system uses. AI Agent SBOM and LLM Mapping delivers a model and vendor register, an AI SBOM, and an LLM data-flow map. Typical sprint: 1 day.

Q: How does RealGround run AI red teaming?
A: Run structured tests for prompt injection, jailbreaks, data leakage, tool misuse, retrieval abuse, and unsafe outputs. RealGround uses Promptfoo test suites, Garak scans and custom payloads, and delivers a fix-prioritized report. Typical sprint: 1 week.

Q: How long does an engagement take?
A: Typical sprints: AI Agent SBOM and LLM Mapping 1 day, AI Red Teaming 1 week, Secure AI Agent Build 8 weeks.

Q: What do I get at the end of an engagement?
A: Engineering artifacts your team can put into tickets and reviews: agent permission matrices, approval gates and tool-risk reviews; model registers, vendor lists, data-flow maps and AI SBOMs; Promptfoo tests, Garak scans, attack cases, findings and prioritized fixes.

Q: Is there a free AI agent security scanner?
A: Yes. The RealGround AI Agent Security Scanner (beta) is free. It checks a GitHub repo, ZIP upload, or live chatbot for LLM usage, generates an AI SBOM with CVE findings, and runs prompt-injection and jailbreak probes.

Q: What can the RealGround scanner scan?
A: A GitHub or GitLab repository, a ZIP upload of your code, or a live chatbot URL.

Q: What does the scanner check?
A: It maps LLM usage and prompts in code, discovers API endpoints (Flask, FastAPI, Django, Express, NestJS), lists outbound APIs and integrations, looks for secrets, generates an SBOM with Syft and checks dependencies for known CVEs with Grype. For live chatbots it runs prompt-injection and jailbreak tests with Promptfoo and Garak.

Q: What is in a scanner report?
A: A security score out of 100 with a grade, a fix-first list, a can-I-ship verdict, an AI-written summary, an architecture map of your agent's entry points, integrations and data stores, and the full findings list. Reports can be downloaded as PDF.

Q: Do I need an account to use the scanner?
A: Yes. You sign up with an email address; your scan history is kept in your account.

Q: When should I use the scanner, and when should I engage RealGround?
A: Use the scanner for a fast self-service first pass. Engage RealGround when you need the full picture: AI Agent SBOM and LLM Mapping for a complete inventory, AI Red Teaming for structured adversarial testing, or Secure AI Agent Build to design the controls.

## Machine-Readable Resources
- llms.txt (short version): https://www.realground.com/llms.txt
- Services Schema: https://www.realground.com/ai-services.json
- Risk-to-Service Mapping: https://www.realground.com/security-offerings.json
- Agent Context API: https://www.realground.com/api/v1/agent-context
- OpenAPI Manifest: https://www.realground.com/openapi.json
- Sitemap: https://www.realground.com/sitemap.xml
- Site Directory: https://www.realground.com/sitemap

## Contact
- Advisory inquiries: https://www.realground.com/contact
- Email: advisory@realground.com