Protect Attorney-Client Privilege
Secure AI legal tools while maintaining confidentiality and professional ethics
About AI Security in Legal
Law firms and legal departments are adopting AI for document review, legal research, contract analysis, and client communication. These applications must protect attorney-client privilege, work product doctrine, and comply with bar association ethics rules. Wardstone ensures legal AI maintains confidentiality while preventing data leakage that could waive privilege.
AI Security Challenges in Legal
Privilege Protection
AI systems handling case files risk waiving attorney-client privilege through data leakage or unauthorized disclosure.
Confidentiality Breaches
Legal AI processing sensitive case information must prevent exposure to opposing counsel or public disclosure.
Ethics Compliance
Bar associations require lawyers to maintain competence in technology and protect client information.
Multi-Client Isolation
Law firms serving multiple clients must ensure AI doesn't leak information between matters.
Use Cases for Legal
Document Review
Secure AI-assisted document review and e-discovery
Legal Research
Protect AI legal research tools processing case files
Contract Analysis
Secure AI contract review and negotiation assistance
Client Communication
Protect AI-powered client portals and intake systems
Compliance Support
ABA Model Rules
American Bar Association rules on confidentiality and competence
Wardstone helps lawyers meet their duty of technological competence by securing AI tools against attacks.
Attorney-Client Privilege
Legal protection for confidential communications between lawyer and client
Data leakage detection prevents inadvertent disclosure that could waive privilege.
Work Product Doctrine
Protection for materials prepared in anticipation of litigation
Output filtering ensures case strategy and analysis aren't exposed through AI responses.
Legal AI Security Architecture
Privilege-aware security for legal AI applications
Threats We Protect Against
Data Leakage
highUnintended exposure of sensitive information, training data, or system prompts through LLM outputs. Ranked as LLM02 in the OWASP Top 10 for LLM Applications 2025, up from #6 in the 2023 edition, reflecting its growing real-world impact.
PII Exposure
highThe unintended disclosure of Personally Identifiable Information (PII) such as names, addresses, SSNs, credit cards, or other personal data through LLM interactions. Falls under OWASP LLM02:2025 (Sensitive Information Disclosure).
Prompt Injection
criticalAn attack where malicious instructions are embedded in user input to manipulate LLM behavior and bypass safety controls. Ranked as LLM01 in the OWASP Top 10 for LLM Applications 2025 and cataloged by MITRE ATLAS as technique AML.T0051.
System Prompt Extraction
highTechniques used to reveal the hidden system prompt, instructions, or configuration that defines an LLM application's behavior. Introduced as a standalone category in OWASP LLM07:2025 (System Prompt Leakage), new to the 2025 edition.
Related Industry Solutions
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