Tagged "local-llm-security"
8 articles tagged local-llm-security, 28 March 2026 to 2 June 2026. Newest first.
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Supply Chain DLP: Stop Leaked .env Files, Credentials, SSH Keys, and API Tokens
A security-focused tool and framework for preventing credential leaks in development and deployment pipelines, critical for teams running local LLMs with sensitive infrastructure.
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llama.cpp GGUF Parser Flaws: Critical Integer Overflow Enables Arbitrary Reads in Every Local AI Stack
A critical security vulnerability discovered in llama.cpp's GGUF parser threatens the integrity of local LLM deployments. The flaw allows attackers to read arbitrary memory through malicious model files.
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AI Guardrails Stripped From Meta and Google Models in Minutes
Security researchers demonstrate vulnerabilities allowing rapid removal of safety guidelines from commercial LLMs. Critical implications for organizations relying on guardrails in locally-deployed or fine-tuned models.
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Ollama Out-of-Bounds Read Vulnerability Allows Remote Process Memory Leak
A critical vulnerability in Ollama's GGUF parser enables remote attackers to read sensitive process memory, potentially exposing model weights and user data. This vulnerability affects all versions of Ollama and requires immediate patching for production deployments.
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On-Device Apple Intelligence Vulnerable to Prompt Injection Attacks
Security researchers have discovered that Apple's on-device AI system is susceptible to prompt injection techniques, raising important questions about the security model of local LLM deployments.
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Privilege Escalation Attacks on GPUs Using Rowhammer
Security researchers document rowhammer-based privilege escalation vulnerabilities affecting GPUs, raising important security considerations for anyone running sensitive workloads on local GPU infrastructure.
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Miasma: A Tool to Protect Data from AI Web Scrapers
Miasma, a new open-source tool that creates adversarial noise to trap and confuse AI web scrapers, helps protect locally-hosted content and APIs from unauthorized data harvesting.
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Prompt Security Challenges Emerge as Critical Concern for Local LLM Deployments
Security researchers highlight prompt injection and adversarial prompt vulnerabilities as significant risks for locally deployed LLMs, requiring careful consideration of input validation and defensive measures in production inference systems.