756 matches found
Detecting and analyzing prompt abuse in AI tools
This second post in our AI Application Security series is all about moving from planning to practice. AI Application Series 1: Security considerations when adopting AI tools established how AI adoption expands the attack surface and our threat-modelling guidance on the Microsoft security blog...
DRUPAL-CONTRIB-2026-028
The module and certain submodules AI Automators, AI Translate, AI API Explorer, AI Content Suggestions provide the ability to use an LLM to generate HTML or Markdown and preview it in a browser. Under certain circumstances, rendering of this HTML can lead to exposing secret communications in the...
AttriGuard: Defeating Indirect Prompt Injection in LLM Agents Via Causal Attribution of Tool Invocations
LLM agents are highly vulnerable to Indirect Prompt Injection IPI, where adversaries embed malicious directives in untrusted tool outputs to hijack execution. Most existing defenses treat IPI as an input-level semantic discrimination problem, which often fails to generalize to unseen payloads. We...
rami-kali-MCP
Red Team MCP Server MCP Model Context Protocol server that...
CLIOPATRA: Extracting Private Information from LLM Insights
As AI assistants become widely used, privacy-aware platforms like Anthropic's Clio have been introduced to generate insights from real-world AI use. Clio's privacy protections rely on layering multiple heuristic techniques together, including PII redaction, clustering, filtering, and LLM-based...
Evaluating Generalization Mechanisms in Autonomous Cyber Attack Agents
Autonomous offensive agents often fail to transfer beyond the networks on which they are trained. We isolate a minimal but fundamental shift -- unseen host/subnet IP reassignment in an otherwise fixed enterprise scenario -- and evaluate attacker generalization in the NetSecGame environment. Agent...
Targeted Bit-Flip Attacks on LLM-Based Agents
Targeted bit-flip attacks BFAs exploit hardware faults to manipulate model parameters, posing a significant security threat. While prior work targets single-step inference models e.g., image classifiers, LLM-based agents with multi-stage pipelines and external tools present new attack surfaces,...
OpenAnt LLM-Based Vulnerability Discovery
OpenAnt from Knostic is an open source LLM-based vulnerability discovery product that helps defenders proactively find verified security flaws while minimizing both false positives and false negatives. Stage 1 detects. Stage 2 attacks. What survives is real...
SUSE CVE-2026-25802
New API is a large language mode LLM gateway and artificial intelligence AI asset management system. Prior to version 0.10.8-alpha.9, a potential unsafe operation occurs in component MarkdownRenderer.jsx, allowing for Cross-Site ScriptingXSS when the model outputs items containing tag. Version...
CVE-2025-12345 LLM-Claw Agent Deployment initiate.c agent_deploy_init buffer overflow
A security vulnerability has been detected in LLM-Claw 0.1.0/0.1.1/0.1.1a/0.1.1a-p1. The affected element is the function agentdeployinit of the file /agents/deploy/initiate.c of the component Agent Deployment. Such manipulation leads to buffer overflow. It is possible to launch the attack...
CVE-2025-12345 LLM-Claw Agent Deployment initiate.c agent_deploy_init buffer overflow
A security vulnerability has been detected in LLM-Claw 0.1.0/0.1.1/0.1.1a/0.1.1a-p1. The affected element is the function agentdeployinit of the file /agents/deploy/initiate.c of the component Agent Deployment. Such manipulation leads to buffer overflow. It is possible to launch the attack...
Jailbreak Foundry: From Papers to Runnable Attacks for Reproducible Benchmarking
Jailbreak techniques for large language models LLMs evolve faster than benchmarks, making robustness estimates stale and difficult to compare across papers due to drift in datasets, harnesses, and judging protocols. We introduce JAILBREAK FOUNDRY JBF, a system that addresses this gap via a...
Neurosymbolic Learning for Advanced Persistent Threat Detection under Extreme Class Imbalance
The growing deployment of Internet of Things IoT devices in smart cities and industrial environments increases vulnerability to stealthy, multi-stage advanced persistent threats APTs that exploit wireless communication. Detection is challenging due to severe class imbalance in network traffic,...
CVE-2026-3071
Deserialization of untrusted data in the LanguageModel class of Flair from versions 0.4.1 to latest are vulnerable to arbitrary code execution when loading a malicious model...
CVE-2026-3071
The CVE concerns Flair’s LanguageModel class where deserialization of untrusted data in versions 0.4.1 to latest allows arbitrary code execution when loading a malicious model. The issue, with CVSSv3.1 metrics indicating HIGH severity (Local access, no user interaction, full scope and high confid...
PT-2026-22151
Name of the Vulnerable Software and Affected Versions Flair versions 0.4.1 through latest Description The deserialization of untrusted data in the LanguageModel class can lead to arbitrary code execution when loading a malicious model. Recommendations Versions prior to 0.4.1 are not affected. At...
flair 安全漏洞
Flair is a very simple and advanced NLP framework developed by Flair OpenSource. There are security vulnerabilities in Flair versions 0.4.1 onwards. These vulnerabilities stem from the LanguageModel class’s ability to deserialize untrusted data, which may allow arbitrary code to be executed when...
CVE-2026-25802
New API is a large language mode LLM gateway and artificial intelligence AI asset management system. Prior to version 0.10.8-alpha.9, a potential unsafe operation occurs in component MarkdownRenderer.jsx, allowing for Cross-Site ScriptingXSS when the model outputs items containing...
CVE-2026-25802
New API is a large language mode LLM gateway and artificial intelligence AI asset management system. Prior to version 0.10.8-alpha.9, a potential unsafe operation occurs in component MarkdownRenderer.jsx, allowing for Cross-Site ScriptingXSS when the model outputs items containing tag. Version...