Pii
PulseAugur coverage of Pii — every cluster mentioning Pii across labs, papers, and developer communities, ranked by signal.
5 day(s) with sentiment data
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AI Gateways Enhance Data Security for ChatGPT and Claude Usage
Organizations are implementing Data Loss Prevention (DLP) strategies to prevent sensitive data from being exposed when using third-party Large Language Models (LLMs) like ChatGPT and Claude. An AI gateway, such as Bifro…
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Automated redaction secures sensitive data for LLM use
To mitigate security and compliance risks when using LLMs like those from OpenAI, Anthropic, and Google, sensitive data must be redacted before being sent in prompts. This involves automated inline prompt redaction, whi…
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AI security: Multi-layered approach to prevent sensitive data leakage
Organizations must implement a multi-layered security strategy to prevent sensitive data from being sent to third-party AI tools. This involves identifying and classifying data such as PII, PHI, secrets, and intellectua…
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Local AI cascade achieves high accuracy in de-identifying educational dialogue
Researchers have developed a novel AI cascade framework designed to de-identify sensitive educational dialogue while preserving valuable content. This local system addresses the limitations of commercial LLMs, which req…
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Enterprise AI assistants secured with new MCP gateway to prevent data leaks
Enterprises are grappling with the security and compliance risks associated with AI assistants, particularly concerning the leakage of sensitive code and Personally Identifiable Information (PII). To address this, a new…
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Text-to-SQL LLM risks: Data leaks and cost overruns
The notion that Text-to-SQL is a solved problem is a dangerous myth, as LLMs can generate non-deterministic SQL queries that pose risks to sensitive data. Approaches like feeding the entire schema to the LLM or using se…
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Redact PII in LLM Traces with Centralized Span Processor
A new approach to redacting Personally Identifiable Information (PII) from LLM application traces focuses on a centralized span processor rather than modifying individual call sites. This method ensures consistent PII s…
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AI PII Safety Needs More Than Prompt Instructions
A recent analysis argues that relying solely on prompt instructions is insufficient for ensuring Personally Identifiable Information (PII) safety within AI systems. The author proposes a more robust approach, emphasizin…
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RAG security: Retrieval-stage access control is key, not output masking
A technical article argues that masking Personally Identifiable Information (PII) at the output stage of a Retrieval-Augmented Generation (RAG) system is an insufficient security measure. The author explains that by the…
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New local LLM nears frontier PII removal at 9ms CPU inference
A new local language model has been developed that demonstrates near-frontier performance in removing Personally Identifiable Information (PII) from computer usage data. This model achieves this with a rapid inference t…
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DeBERTa model achieves broad PII detection with simple fine-tuning
Researchers have developed a new approach to personally identifiable information (PII) detection using DeBERTa models, achieving a significant improvement in broad-coverage detection across diverse text sources. Their s…
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On-device PII substitution pipeline uses locale-prompting to fix regurgitation
Researchers have developed an on-device pipeline for substituting Personally Identifiable Information (PII) with consistent, type-preserving fake values, aiming to maintain downstream text utility. The system uses a sma…
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New tool checks LLM prompt data leaks; game studio hires AI creator
A new free tool has been developed to help users identify and prevent Personally Identifiable Information (PII) from being leaked in their LLM prompts. Meanwhile, the studio behind the game "Lies of P" is seeking an "AI…
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New algorithm reconstructs PII from finetuned language models
Researchers have developed a new decoding algorithm called COVA to reconstruct personally identifiable information (PII) from supervised finetuned language models. The study focused on sensitive domains like medical and…
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LLMs enable taxonomy-agnostic PII annotation in HTTP traffic
Researchers have developed a novel pipeline utilizing Large Language Models (LLMs) to automatically identify and annotate Personally Identifiable Information (PII) within HTTP traffic. This method aims to overcome the l…
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PIIGuard shields webpages from LLM PII harvesting via adversarial fragments
Researchers have developed PIIGuard, a novel webpage-level defense system designed to prevent large language models (LLMs) from harvesting personally identifiable information (PII). This system embeds hidden HTML fragme…
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LLM prompts pose quiet PII leak risk, experts warn
A recent analysis highlights a significant privacy concern regarding Large Language Models (LLMs), specifically how user prompts can be inadvertently leaked. This issue stems from the way LLMs process and potentially st…
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OpenAI's new PII model enhances privacy filter for echo.apperdeck.com
The privacy filter tool echo.apperdeck.com has integrated OpenAI's newest PII model. This model is designed for local, open-weight operation, focusing on masking personal data. The integration aims to enhance user priva…
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OpenAI releases Privacy Filter for local PII detection and redaction
OpenAI has released Privacy Filter, an open-weight model designed to detect and redact personally identifiable information (PII) from text. This tool is built to run locally, offering enhanced privacy by processing data…