LLM security is not only detecting prompt injections 🏴☠️🚩 We published a breakdown of the three main attack categories used to test conversational AI agents: → Single-turn attacks attempt to manipulate the model in one shot disguised requests or role-playing prompts. → Multi-turn attacks build context over multiple interactions, achieving higher success rates by gradually escalating toward the objective. → Dynamic agentic attacks use autonomous agents that adapt in real-time, reaching 90%+ success rates against top models by learning from each response. The article covers: - Specific techniques for each attack type with examples - Why multi-turn methods bypass defenses that single-turn attempts - How to implement AI red teaming attacks Article 👉 https://lnkd.in/eMSQqvqn #LLMSecurity #AIRedTeaming #LLMjailbreaking
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Every week we publish another AI Explainer series (with topics like: context rot, data extraction, agent misalignment, open-vs-closed models, etc.), but I find that one of the most important topics that has been coming up lately is the video we did a few weeks ago on agentic security and specifically what happens when attackers target agents with prompt injection / data poisoning: https://lnkd.in/gNt7MJ9g I hope that all platforms who use agents will take precautions to protect against attacks, but until that happens it is incredibly easy to trick AI Agents into doing bad things and it will naturally continue to threaten AI adoption in enterprises.
When AI Gets Tricked: Understand Prompt Injection & Data Poisoning | Box AI Explainer Series EP 16
https://www.youtube.com/
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Freelance copywriting, editing, customer storytelling, content marketing, and AI-assisted content development (“human in the loop”) for technology companies and B2B brands doing good things in innovative ways.
If you're looking to play technical catchup with your understanding of basic generative and agentic AI, here's a good place to start. This weekly Box podcast with CTO Ben Kus is succinct and entertaining.
Every week we publish another AI Explainer series (with topics like: context rot, data extraction, agent misalignment, open-vs-closed models, etc.), but I find that one of the most important topics that has been coming up lately is the video we did a few weeks ago on agentic security and specifically what happens when attackers target agents with prompt injection / data poisoning: https://lnkd.in/gNt7MJ9g I hope that all platforms who use agents will take precautions to protect against attacks, but until that happens it is incredibly easy to trick AI Agents into doing bad things and it will naturally continue to threaten AI adoption in enterprises.
When AI Gets Tricked: Understand Prompt Injection & Data Poisoning | Box AI Explainer Series EP 16
https://www.youtube.com/
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Indirect Tool Injection Attacks occur when attackers manipulate external tools or services that interact with AI systems, causing the AI to behave maliciously without directly altering the system. This type of attack undermines trust in AI by exploiting its dependencies. #AISecurity #CyberThreats #AdversarialAI #AIIntegrity
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Most identity programs don’t need a new tool. They need to make the one they already have smarter. The future of identity security is not about replacing tools, people or workflows - it's about enhancing them with AI. We found 5 reasons why AI augmentation will define the next generation of identity governance; from real-time visibility and contextual decisions to precision that learns from real access patterns. Which of the five you think resonates the most? #AI #IdentitySecurity #IGA #AIAugmentation #IdentityGovernance #FabrixSecurity Nicole Morero
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🚨 𝗧𝗵𝗲 𝗱𝗮𝗿𝗸 𝘀𝗶𝗱𝗲 𝗼𝗳 𝗔𝗜 𝗶𝘀𝗻’𝘁 𝘀𝗰𝗶𝗲𝗻𝗰𝗲 𝗳𝗶𝗰𝘁𝗶𝗼𝗻.. I𝘁’𝘀 𝘁𝗼𝗱𝗮𝘆’𝘀 𝗵𝗲𝗮𝗱𝗹𝗶𝗻𝗲.. With deepfakes fooling millions and prompt injections breaching even the smartest systems, the risks of AI misuse are closer than you think. At WizSumo AI, we’re not just raising the alarm, we’re architecting the solutions. 🔗 Discover in our latest blog: 🠒 Shocking true stories from 2024’s deepfake election chaos and AI hacks 🠒 Why old-school security fails against clever prompt attacks 🠒 How advanced, ethical guardrails are reshaping AI protection.. turning uncertainty into trust 🠒 The roadmap toward safer, responsible AI for everyone Guardrails aren’t just tech, they’re trust. Let’s guide AI safely together.. 👀 Dive into the piece : https://lnkd.in/gNTDtw6a #WizSumo #AIMisuse #AIsecurity #Deepfakes #PromptInjection #AIguardrails #ResponsibleAI
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AI security isn’t just about the models — it’s about the identities behind them. In this clip, Permiso CTO Ian Ahl shows how we’re identifying “overly permissive AI” exposures — like an AI agent with 650 permissions but only using five. Our approach helps teams cut through AI sprawl, surface unnecessary access, and strengthen identity hygiene across AI ecosystems. 🎥 Watch Ian explain how Permiso turns runtime visibility into actionable insights for securing AI identities.
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*** Beyond awareness: engineering resilience against Shadow AI *** Unmanaged AI use is creating invisible vulnerabilities in organizations. This article explains how to identify, contain, and control shadow AI before it undermines resilience.... https://lnkd.in/e9AftnZc #ShadowAI #ArtificialIntelligence #RiskManagement
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Risks and challenges using Generative AI : ---------------------------------------------- 1.Misuse by adversaries: The same capabilities that benefit defenders can be used by criminals for malicious purposes. 2.Data poisoning attacks: Attackers can deliberately inject bad data into training sets to manipulate the behavior of AI models. 3.Emergence of new attack vectors: The technology itself creates new risks that require new security measures to address.
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The AI Trust Paradox: Why Security Teams Fear Automated RemediationTyler ShieldsSecurity teams are investing in AI for automated remediation yet express concerns over trusting the technology due to potential unintended consequences and the opacity of AI processes.https://https://lnkd.in/esngfsYy
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Every AI jailbreak assumes the model thinks the same way. What if you could change how it thinks without breaking anything else? Researchers just cracked this puzzle with "LLM salting." The technique borrows from password security. It rotates how AI models recognize harmful prompts internally. The results are impressive: 🔒 Attack success dropped from 100% to under 3% 🚀 Model performance stayed intact 🛡️ Beats traditional defenses by miles Here's why this matters. Most jailbreak attacks rely on precomputed prompts that work across similar models. Salting breaks that assumption. It changes the "refusal direction" in the model's activation space. Think of it as rewiring how the AI processes potentially harmful requests. The beauty? Your chatbot still works perfectly for legitimate use cases. This research from the 2025 CAMLIS conference shows we can have both security and functionality. We don't need to choose. As AI becomes more widespread, techniques like this will be crucial. They protect users without sacrificing the experience we've come to expect. What's your take on balancing AI safety with performance? #AISecuridade #MachineLearning #AISafety 𝐒𝐨𝐮𝐫𝐜𝐞: https://lnkd.in/euKKkF4G
