18 matches found
open-source-llm-scanners
open-source-llm-scanners A list of open source LLM security scanners on GitHub, ordered by Stars. It does not provide in-depth analysis. A minimum of 10 stars are needed as a low bar 😁 Related: open-source-web-scanners LLM Scanners Tools which can find a range of vulnerabilities in LLM...
DonkAI
Hands-on lab for the OWASP Top 10 for LLM Applications 2025 - no real LLM required. DonkAI is deliberately vulnerable web app you can run in one command and use to learn how LLM-integrated systems get broken by actually breaking them. Every OWASP LLM Top 10 category is represented by at least one...
SecureAI-Scan
SecureAI-Scan Offline CLI that scans TypeScript, JavaScript, and Python for LLM, MCP, Agent Skill, and RAG risks — import-resolved dataflow evidence, zero default false positives, mapped to OWASP LLM/ASI/MCP Top 10. Most scanners in this space pattern-match a keyword and call it a finding...
reasongate
ReasonGate A self-hostable gate that inspects the text going into and out of an LLM and returns an explainable allow / flag / block decision with a machine-readable audit record for every call. What this is The open-source core is rule-based. It does four things: recognizes known prompt-injection...
aco-prompt-shield
aco-prompt-shield 🛡️ Stop prompt injection attacks before they reach your LLM — zero API costs, runs entirely locally, integrates in 2 minutes. Prompt injection is the 1 security risk for LLM applications. aco-prompt-shield catches known jailbreak patterns, understands semantic intent via ML, and...
OpenHunterAI
OpenHunterAI Your local AI red team. Attacker-style reasoning for web, API, and LLM application security. Quick start · Agent skill · Assessment model · Architecture · Docs · Star history OpenHunterAI brings scope, scan activity, findings, and remediation into one local workspace. Start without a...
LLM-MCP-Security-Field-Guide
🛡️ AI Security Field Guide — LLM + MCP Security The most comprehensive, up-to-date, practitioner-first security reference for LLM applications and Model Context Protocol MCP deployments. Covers real CVEs, live attack patterns, OWASP frameworks, red teaming tools, and actionable checklists — update...
cover
Cover Keep private data, internal infrastructure and secrets out of cloud coding agents without breaking your workflow. Install · Quick start · Policies · Monitoring · Pi / OMP · Security Cover is a bidirectional privacy proxy for AI coding agents. It replaces matched sensitive values locally wit...
llm-prompt-injection-resources
llm-prompt-injection-resources Una colección seleccionada de recursos para aprender e investigar sobre ataques de inyección de prompts en LLM, defensas y seguridad. Donar Apoya el mantenimiento de este proyecto con PayPal o escaneando el código QR a continuación...
bordair-detector
Bordair Detector A two-stage detector for prompt injection and jailbreak attempts in LLM inputs. A regex gate settles the easy majority of traffic without touching the model; anything ambiguous falls through to a quantised DeBERTa-v3 classifier running in ONNX. The same engine covers image,...
llm-security-101
Seguridad de LLM 101 Adentrándonos en el ámbito de la seguridad de LLM: una exploración de herramientas ofensivas y defensivas, revelando sus capacidades actuales. A medida que adoptamos los Modelos de Lenguaje de Gran Tamaño LLM en diversas aplicaciones y funcionalidades, es crucial comprender l...
Risk-Adjusted Harm Scoring for Automated Red Teaming for LLMs in Financial Services
The rapid adoption of large language models LLMs in financial services introduces new operational, regulatory, and security risks. Yet most red-teaming benchmarks remain domain-agnostic and fail to capture failure modes specific to regulated BFSI settings, where harmful behavior can be elicited...
CacheTrap: Injecting Trojans in LLMs without Leaving Any Traces in Inputs or Weights
Adversarial weight perturbation has emerged as a concerning threat to LLMs that either use training privileges or system-level access to inject adversarial corruption in model weights. With the emergence of innovative defensive solutions that place system- and algorithm-level checks and correctio...
CAVGAN: Unifying Jailbreak and Defense of LLMs Via Generative Adversarial Attacks on Their Internal Representations
Security alignment enables the Large Language Model LLM to gain the protection against malicious queries, but various jailbreak attack methods reveal the vulnerability of this security mechanism. Previous studies have isolated LLM jailbreak attacks and defenses. We analyze the security protection...
JavelinGuard: Low-Cost Transformer Architectures for LLM Security
We present JavelinGuard, a suite of low-cost, high-performance model architectures designed for detecting malicious intent in Large Language Model LLM interactions, optimized specifically for production deployment. Recent advances in transformer architectures, including compact BERTDevlin et al...
CVE-2025-23254
NVIDIA TensorRT-LLM for any platform contains a vulnerability in python executor where an attacker may cause a data validation issue by local access to the TRTLLM server. A successful exploit of this vulnerability may lead to code execution, information disclosure and data tampering...
Qualys TotalAI: The Journey from LLM Scanner to Comprehensive AI Security Solution
Embarking on the AI/ML Journey The launch of Qualys TotalAI marks a significant milestone in our journey with AI/ML. It all began in March 2024 when we ventured into the rapidly evolving AI/ML landscape and the emerging LLM ecosystem. Recognizing the potential of these technologies to revolutioni...
