MITRE ATLAS™ (Adversarial Threat Landscape for Artificial-Intelligence Systems) is a globally accessible, living knowledge base of adversary tactics and techniques based on real-world attack observations and realistic demonstrations from AI red teams and security groups. There are a growing number of vulnerabilities in AI-enabled systems, as the incorporation of AI increases the attack surface of existing systems beyond those of traditional cyber-attacks.
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MITRE | ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) is a globally accessible, living knowledge base of adversary TTPs based on real-world attack observations and realistic demonstrations from AI red teams and security groups.
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Increased context windows in LLMs are great. But here is a jailbreaking technique that exploits exactly that. It uses many-shot learning: hundreds of demonstrations to steer model behavior. Many-shot Jailbreaking (MSJ) is a direct long-context attack that exploits multiple instances of undesirable behaviors. The effectiveness of these attacks increases according to a power law to the number of examples provided! Despite altering the format or content of the prompts, mitigating these attacks remains challenging, suggesting that very long contexts unveil a new vector for adversarial strategies against LLMs. The study uncovers that models of larger sizes tend to be more susceptible to many-shot jailbreaking, complicating the task of safeguarding them without diminishing their capabilities. Blog post: https://lnkd.in/ex4TvDsD Paper: https://lnkd.in/ef2DWa7H
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#ICYMI, our top OSINT videos from March showcased weekly demonstrations on how to utilize the Forensic OSINT Chrome Extension along with another OSINT tool. These are the OSINT tools we highlighted: ✅ Wayback Machine 🕰️ ✅ Add-on: Fake News Debunker 🕵️♂️ ✅ Whoxy 🔍 ✅ Whatsmymame 🤔
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Innovating Computing & Technology Solutions For Complex Problems! | Product Strategy & Management | Driving 20+ Years of Engineering, Impactful Solutions & Mentorship.
Psst, did you know that here at Ace Computers we are a leading technology provider for the Forensics, Intelligence, and Data Extraction/Analysis communities? Not only do we excel in HPC and other computing solutions, but our technology solutions go above and beyond for our Law Enforcement and Federal Agencies. #AI #Intelligence #HPC #Forensics
Ace Computers will be at the RISS Conference next week, showcasing our latest innovation - the Ace FORCE 5 Forensic Examiner & Investigator Series, a Mobile Extraction & Triage Unit! Join us to explore the cutting-edge features of the Ace FORCE 5, designed to revolutionize mobile data extraction and triage for forensic investigations. With its advanced capabilities, this unit empowers investigators with rapid and efficient extraction of crucial digital evidence, ensuring thorough examination and analysis. Our team will be on hand to provide live demonstrations and answer any questions you may have. Don't miss this opportunity to witness the future of forensic technology in action! #ForensicTechnology #DigitalInvestigation #AceComputers #RISSConference
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Data Scientist Michael Ryaboy discusses KDB.AI's Temporal Similarity Search (TSS) and how it accelerates real-time data analysis in this recent live event. Michael shows how TSS helps developers conduct near real-time similarity searches on rapidly evolving time-series data. Watch now for code demonstrations of Transformed TSS and Non-Transformed TSS. Stream the entire event: https://lnkd.in/enHgwHVX #KX #KDBAI #TSS #DataAnalysis #DataInsights #RealTimeAnalytics
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enabling digital services for Student Loan related activities while maintaining the highest security standard, the most compliant personal data protection and customer-centric data-driven innovation.
🔗 Exciting news! Check out this insightful blog post on "Any-point Trajectory Modeling for Policy Learning," which presents a novel framework called Any-point Trajectory Modeling (ATM). This framework leverages video demonstrations to pre-train a trajectory model, enabling the prediction of future trajectories of arbitrary points within a video frame. With minimal action-labeled data, this approach facilitates the learning of robust visuomotor policies. Dive into the details and explore the visualizations and code at: https://bit.ly/3H1Ty6r.
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Seven minutes are all it takes for the fastest adversary to break out and start moving laterally. Experience a live demonstration of CrowdStrike Falcon LogScale to learn how to triage, investigate and respond to STARDUST CHOLLIMA. https://lnkd.in/ei4kYqxb
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