newsVentureBeatTrust 60Published 1mo agoLive · 1mo ago
Prompt injection is exploiting enterprise AI's biggest design flaws by targeting agents, RAG pipelines and model routers
In the past two years, businesses have been trying to fit large language models (LLMs) into support, analytics, development, and internal automation like never before. Along with the increasing adoption of AI technology , another trend is gaining momentum — cybercriminals are taking advantage of the disconnect between assumptions about LLMs and their actual c
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Covers
repoagent-toolsarticleA field guide to AI agents in 2026paperPrompt Injection in Automated Résumé Screening with Large Language Models: Single and Multi-Injection SettingspaperBeyond Surface Forms: A Comprehensive, Mechanism-Oriented Taxonomy of Indirect Linguistic Encoding for LLM-Based Coded Language DetectionpaperAgent-Native Immune System: Architecture, Taxonomy, and Engineering
Covers (incoming)
paperFrom Tokens to States: LLMs as a Special Case of World Models and the Continuous Path Beyondrepodchatterjee01-prog/analyticaospaperDirect Causation in International Humanitarian Law and the Challenge of AI-Mediated Civilian Cyber OperationspaperPolicyGuard: A Dialogue-Grounded Sub-Agent Verifier for Policy Adherence in LLM AgentspaperManufactured Confidence: How Memory Consolidation Turns Hearsay into Confident FactspaperEvalSafetyGap: A Hybrid Survey and Conceptual Framework for LLM Evaluation-Safety FailurespaperMulti-Agentic System Leveraging Open-Source LLMs to Mitigate Disinformation ThreatspaperEntity Binding Failures in Tool-Augmented AgentspaperLinguistic Firewall: Geometry as Defense in Multi-Agent Systems RoutingpaperWords Speak Louder Than Code: Investigating Cognitive Heuristics in LLM-Based Code Vulnerability DetectionpaperWhen the Database Fails: Prompting LLM Dialogue Agents for Safe Recovery in Task-Oriented DialoguepaperFLARE-AI: Flaw Reporting for AIpaperA Lifecycle and Application-Stack Survey of Large Language Model Vulnerabilities: Attacks, Risks, Defenses, and Open ProblemspaperTheory of Mind and Persuasion Beyond Conversation: Assessing the Capacity of LLMs to Induce Belief States via Planning and ActionpaperBehavior-Adaptive Conversational Agents: Toward a Fluid Personality FrameworkpaperAgentic generation of verifiable rules for deterministic, self-expanding reaction classificationpaperConversable Complexity: Agentic LLM Collectives as Interpretable SubstratespaperDistill to Detect: Exposing Stealth Biases in LLMs through Cartridge DistillationrepoAgustiPuigserver/opus-prompt-architectrepopromptfoo/promptfoorepoProductive-Superintelligence/lllmrepoBigBoySlave/Agents-PromptspaperBehind the Refusal: Determining Guardrail Activation via Behavioral MonitoringpaperUA-ChatDev: Uncertainty-Aware Multi-Agent Collaboration for Reliable Software DevelopmentpaperSkillFuzz: Fuzzing Skill Composition for Implicit Intents Discovery in Open Skill Marketplacesrepoyegor256/promptrepoaircrushin/promptMinderrepolegeling/PromptHubrepoexpectedparrot/edslrepokoji/LLM-PromptEngineering-Agentsrepolinshenkx/prompt-optimizerrepoadenaufal/anti-slop-writingrepoai-village-agents/village/llm-psychoactive-promptsrepotruefoundry/modelsrepoanmolksachan/AI-ML-Free-Resources-for-Security-and-Prompt-InjectionpaperAutomated Compliance Mapping in Cloud Security with Domain-Adapted Sentence TransformerspaperToken-Flow Firewall: Semantic Runtime Auditing for Persistent AI AgentspaperLLM for EDA in Front-End Design: Challenges and Opportunitiesrepomicrosoft/PromptKitrepoGreyDGL/PentestGPTpaperTracing Agentic Failure from the Flow of Successrepomrwogu/promptscriptrepohermes-labs-ai/lintlangrepoidvcorreia/engineering-automationsreponurettincoban/ai-prd-workflowrepomicrosoft/LMOpspaperZero Hallucination, by Construction: Hallucination-Aware Layered Oversight for Trustworthy Enterprise AIpaperThey'll Verify. They Just Won't Act. How Authority Framing and Laundered Code Turn a Trusted Agentic CI/CD Pipeline Into an Attack Surfacerepokennethleungty/Finance-LLMspaperThe Ethics of Autonomous AI Agents for Offensive Securityrepocyberupdates365/usa-enterprise-ai-security-threat-vault-2026
Related across the graph
repoProductive-Superintelligence/lllmrepoidvcorreia/engineering-automationspaperAutomated Compliance Mapping in Cloud Security with Domain-Adapted Sentence Transformersrepodchatterjee01-prog/analyticaospaperBeyond Surface Forms: A Comprehensive, Mechanism-Oriented Taxonomy of Indirect Linguistic Encoding for LLM-Based Coded Language DetectionpaperTracing Agentic Failure from the Flow of SuccesspaperMulti-Agentic System Leveraging Open-Source LLMs to Mitigate Disinformation ThreatspaperWords Speak Louder Than Code: Investigating Cognitive Heuristics in LLM-Based Code Vulnerability Detectionrepomicrosoft/LMOpspaperBehind the Refusal: Determining Guardrail Activation via Behavioral MonitoringpaperThe Ethics of Autonomous AI Agents for Offensive SecuritypaperToken-Flow Firewall: Semantic Runtime Auditing for Persistent AI AgentsrepoBigBoySlave/Agents-PromptspaperLinguistic Firewall: Geometry as Defense in Multi-Agent Systems Routingrepoaircrushin/promptMinderrepokennethleungty/Finance-LLMsrepoexpectedparrot/edslrepomicrosoft/PromptKitrepoadenaufal/anti-slop-writingrepolinshenkx/prompt-optimizerrepohermes-labs-ai/lintlangpaperFLARE-AI: Flaw Reporting for AIpaperEvalSafetyGap: A Hybrid Survey and Conceptual Framework for LLM Evaluation-Safety FailurespaperManufactured Confidence: How Memory Consolidation Turns Hearsay into Confident FactspaperLLM for EDA in Front-End Design: Challenges and OpportunitiespaperPolicyGuard: A Dialogue-Grounded Sub-Agent Verifier for Policy Adherence in LLM AgentspaperSkillFuzz: Fuzzing Skill Composition for Implicit Intents Discovery in Open Skill MarketplacesrepoGreyDGL/PentestGPTpaperDistill to Detect: Exposing Stealth Biases in LLMs through Cartridge Distillationrepomrwogu/promptscriptrepotruefoundry/modelsreponurettincoban/ai-prd-workflowpaperDirect Causation in International Humanitarian Law and the Challenge of AI-Mediated Civilian Cyber OperationspaperConversable Complexity: Agentic LLM Collectives as Interpretable SubstratesarticleA field guide to AI agents in 2026paperEntity Binding Failures in Tool-Augmented Agentsrepolegeling/PromptHubrepocyberupdates365/usa-enterprise-ai-security-threat-vault-2026paperThey'll Verify. They Just Won't Act. How Authority Framing and Laundered Code Turn a Trusted Agentic CI/CD Pipeline Into an Attack Surfacerepoyegor256/promptpaperTheory of Mind and Persuasion Beyond Conversation: Assessing the Capacity of LLMs to Induce Belief States via Planning and ActionpaperBehavior-Adaptive Conversational Agents: Toward a Fluid Personality FrameworkpaperUA-ChatDev: Uncertainty-Aware Multi-Agent Collaboration for Reliable Software Developmentrepokoji/LLM-PromptEngineering-AgentspaperPrompt Injection in Automated Résumé Screening with Large Language Models: Single and Multi-Injection Settingsrepoanmolksachan/AI-ML-Free-Resources-for-Security-and-Prompt-InjectionpaperAgent-Native Immune System: Architecture, Taxonomy, and Engineeringrepopromptfoo/promptfoorepoai-village-agents/village/llm-psychoactive-promptsrepoAgustiPuigserver/opus-prompt-architectpaperZero Hallucination, by Construction: Hallucination-Aware Layered Oversight for Trustworthy Enterprise AIpaperA Lifecycle and Application-Stack Survey of Large Language Model Vulnerabilities: Attacks, Risks, Defenses, and Open ProblemspaperFrom Tokens to States: LLMs as a Special Case of World Models and the Continuous Path BeyondpaperWhen the Database Fails: Prompting LLM Dialogue Agents for Safe Recovery in Task-Oriented Dialoguerepoagent-toolspaperAgentic generation of verifiable rules for deterministic, self-expanding reaction classification