Positive Technologies Adds LLM Firewall Module to PT Application Firewall for AI Service Protection

Positive Technologies has developed the LLM Firewall module as part of its PT Application Firewall solution to secure AI services against prompt injection attacks and data leakage. The module inspects both user requests sent to large language models and the responses generated by those models, detecting attempts to bypass restrictions, extract system instructions, or misuse agent capabilities. It specifically targets prompt injections hidden in documents or direct inputs that could override the model's original instructions. Additional detection covers personal data, passwords, access keys, and toxic or prohibited content in both directions of communication. The solution integrates via OpenAI-compatible APIs and is already available in PT AF Cloud, with deployment in PT AF PRO planned for later. Organizations can configure separate policies for different AI services, choosing between monitoring and blocking modes for requests and responses independently.

AntiMalwareTranslated from Russian

Read at source

Positive Technologies has introduced the LLM Firewall module within PT Application Firewall to protect corporate AI services from attacks targeting large language models.

Modern organizations increasingly entrust AI assistants with sensitive documents, customer data, and system access, making it critical to prevent unauthorized control by external actors. The new module analyzes prompts sent to language models and the corresponding outputs, searching for attempts to bypass built-in restrictions, extract system instructions, disclose confidential information, or redirect agent functions for malicious purposes.

One primary focus is countering prompt injection attacks. Malicious instructions can be delivered directly to the bot or concealed within documents that the model processes. While appearing as ordinary text, these inputs aim to appoint the neural network a new controller. The module can either block suspicious interactions or log them for further investigation.

The solution also detects personal data, passwords, access keys, and toxic or prohibited content. Inspection operates bidirectionally, monitoring both inputs to the model and outputs returned to users. This helps prevent leaks caused not only by sophisticated attackers but also by overly cooperative employees.

LLM Firewall is already integrated into PT AF Cloud and connects to application-model exchanges through APIs compatible with OpenAI Chat Completions and Responses. No separate management console is required. The module is scheduled for addition to PT AF PRO for on-premises deployments at a later date.

Administrators can define distinct policies for various AI services, select monitoring or blocking actions, and configure request and response checks independently. All events are forwarded to PT Application Firewall for analysis and incident investigation.

Meridian digestThe week's most consequential security stories, distilled into one briefing.See the digest

More in AI Security

Logical Argument Claims Full Alignment of Superintelligent AGI Is Fundamentally Impossible
Claude Account Bans Linked to IP Reputation, Device Environment and Payment Channels, But No Confirmed Formula
Local LLMs in AppSec: What Open Tools and Models Can Handle in Application Security