Professional AI Prompt Security Assessment and Protection
Detect and Fix Prompt Security Risks in LLM Applications to Prevent Data Breaches and System Abuse.
What Prompt Security Issues Is Your AI Agent Facing?
Sensitive Data Leakage
Identify prompt and dialogue patterns that may lead to leakage of training or environment data, and provide input/output filtering strategies.
Automation Abuse
Prevent automated actions triggered by malicious commands by limiting command scope and adding pre-execution validation.
Misinformation and Harmful Output
Detect vectors that induce the model to generate misleading, false, or harmful content, and provide mitigation and correction strategies.
Potential Risks of Prompt Security Vulnerabilities
Prompt security issues are not just theoretical threats. In production environments, unprotected prompt injection vulnerabilities can lead to the following serious consequences:
- Sensitive Data Leakage: Attackers may craft prompts that induce the model to disclose internal system information, API keys, user data, or training content—leading to data breaches, privacy violations, and regulatory non-compliance.
- Privilege and Operation Misuse: In automated workflows, malicious prompts can trigger unauthorized actions such as sending emails, executing transactions, or modifying configurations—causing direct financial or operational loss.
- Misleading Output and Brand/Reputation Damage: The model may be manipulated to generate false, harmful, or offensive information, potentially misleading users, damaging trust, and resulting in public relations crises or legal action.
- Cascade Failures in Automation Chains: In multi-step automation processes, a single injected prompt may influence downstream actions, causing widespread disruption across interconnected tasks or systems.
- Compliance and Legal Exposure: Leaking protected data or violating industry-specific regulations (e.g., in finance or healthcare) can lead to regulatory penalties, lawsuits, and long-term compliance risks.
- Detection and Attribution Challenges: Complex inputs and evolving dialogue history make it difficult to detect and trace malicious prompts, increasing response times and elevating remediation costs.
- Malicious Use of AI Models: In open API scenarios or third-party integrations, attackers may exploit the model to generate phishing content, malicious scripts, or social engineering templates—turning your AI into a threat vector.
Our evaluation process combines automated detection with manual re-testing: we generate injection vectors, verify triggering conditions, assess the impact scope, and provide actionable mitigation strategies—including input filtering, command whitelisting, dialogue isolation, and regression validation.
How to Implement Prompt Security Protection
Prompt Injection Detection
By combining automated and manual testing, we identify potentially exploitable injection vectors and their triggering conditions.
Security Patching and Protection
Provide actionable mitigation strategies, including input filtering, dialogue management, command whitelisting, and policy-based safeguards.
Compliance Assessment and Training
Provide compliance testing reports and developer training for product and security teams to support long-term prompt security maintenance.
Common Prompt Security Risks
Command Injection Type
Attackers insert system commands or control statements into the input to force the model into executing unauthorized instructions. This type of risk is especially critical in scenarios involving execution or automated backends, potentially leading to system command execution or the triggering of sensitive operations.
Prompt Escape Type
By crafting inputs with special formatting or contextual manipulation, attackers bypass intended security constraints or context-based rules, causing the model to ignore protective prompts and execute malicious requests. Such attacks are especially common in multi-turn dialogues or complex interaction scenarios.
Data Leakage Induction
Attackers prompt the model to recall or expose sensitive data—such as API keys, internal documentation, or user privacy—posing serious compliance and reputational risks. These attacks are particularly dangerous, as leaked data is often irrecoverable once exposed.
Why Choose Us
- Combines public research with proprietary attack datasets to cover both common and emerging prompt injection variants.
- Delivers remediation patches and regression validation reports to support engineering implementation.
- Prioritizes compliance and data security by avoiding risky experiments on production models.