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AI Security / Compliance Framework

OWASP Top 10 for LLM Applications

The OWASP Top 10 for Large Language Model (LLM) Applications is a critical security resource for developers, data scientists, and security teams. It identifies the most significant risks associated with deploying LLM-based systems, ranging from interface manipulation to infrastructure supply chain compromise. Following this framework ensures that AI applications are built with defense-in-depth principles, addressing both traditional web vulnerabilities and unique machine learning threats.

Vulnerability Vector

Manipulation of the LLM's behavior via crafted inputs (Direct or Indirect).

Impact
  • Unauthorized data access
  • Malicious code execution in agents
Vulnerability Vector

Blindly trusting LLM outputs for downstream processing (e.g., in a browser).

Impact
  • Cross-Site Scripting (XSS)
  • Remote Code Execution (RCE)
Vulnerability Vector

Compromising the integrity of the model's knowledge during training.

Impact
  • Reduced model reliability
  • Persistent security backdoors
Vulnerability Vector

Resource-intensive queries designed to exhaust compute or financial budget.

Impact
  • Service outages
  • Massive financial billing spikes
Vulnerability Vector

Exploiting third-party libraries, model registries, or data vendors.

Impact
  • Full infrastructure compromise
  • Deployment of backdoored models
Vulnerability Vector

Verbatim leakage of PII or proprietary secrets from training data.

Impact
  • Exposure of confidential data
  • Privacy law violations (GDPR/HIPAA)
Vulnerability Vector

Lack of strict validation or authorization for LLM-callable tools.

Impact
  • Unauthorized system actions
  • Data exfiltration from internal APIs
Vulnerability Vector

Granting too much authority to an AI agent without human oversight.

Impact
  • Destructive system actions
  • Unauthorized privilege escalation
Vulnerability Vector

Systems failing due to unverified trust in incorrect LLM outputs.

Impact
  • Introduction of logic bugs
  • Safety and liability incidents
Vulnerability Vector

Unauthorized replication or exfiltration of proprietary model assets.

Impact
  • Total loss of Intellectual Property
  • Competitive disadvantage
Security Control

Output Sanitization & Encoding

Treat LLM outputs as untrusted user input and apply strict encoding.

Security Control

Least Privilege Agent Design

Grant tools only the exact permissions needed; avoid 'Admin' tokens.

Security Control

Input Guardrails & Moderation

Use secondary models (e.g., Llama Guard) to filter incoming prompts.

Security Control

Human-in-the-Loop (HITL)

Require manual approval for irreversible actions (payments, deletions).

Ecosystem & Tooling

Testing Tools

  • Garak (Vulnerability Scanner)
  • PyRIT (Red Teaming Toolkit)
  • Promptfoo (Testing & Eval)
  • OWASP AMASS (Discovery)
  • Burp Suite (API testing)
Practical Application

Hands-on Lab Environment

Ready for the practical lab?

Apply the concepts learned in the OWASP Top 10 for LLM Applications course within our virtual terminal environment.

Start Lab Terminal