『AI Security Ops』のカバーアート

AI Security Ops

AI Security Ops

著者： Black Hills Information Security
無料で聴く

Join in on weekly podcasts that aim to illuminate how AI transforms cybersecurity—exploring emerging threats, tools, and trends—while equipping viewers with knowledge they can use practically (e.g., for secure coding or business risk mitigation).© 2025 Black Hills Information Security 政治・政府
エピソード
  • OpenAI / Hugging Face Breach Walkthrough | Episode 65

    OpenAI / Hugging Face Breach Walkthrough | Episode 65
    2026/08/06
    🔒 Want to run AI without sending your data to the cloud?AI Security Ops co-host Bronwen Aker is teaching Keeping Things Local: Build Private LLMs for Your Team.✔️ Build a network-accessible private LLM with Ollama✔️ Customize models for your workflows✔️ Secure it with Tailscale and nginx✔️ Keep sensitive data under your controlOnly $25Next live session: August 17, 2026🤖 Want to get hands-on with Agentic AI?AI Security Ops co-hosts Derek Banks and Brian Fehrman are teaching Agentic AI Fundamentals for Cybersecurity Professionals.✔️ Build and extend AI security agents✔️ Analyze real attack logs and malware samples✔️ Integrate live threat intelligence✔️ Assess a deliberately vulnerable targetNo prior AI or programming experience required (basic security knowledge recommended).Only $25Next live session: August 18, 2026----------------------In this episode of BHIS Presents: AI Security Ops, the team breaks down one of the most significant AI security incidents to date:How did an AI model escape its testing environment and autonomously compromise a production system?This wasn’t a stolen password. It wasn’t a poisoned public model. And it wasn’t a human attacker sitting at a keyboard.Instead, an AI model participating in an internal cyber-capability evaluation reportedly escaped its own sandbox, reached the public internet, and compromised Hugging Face infrastructure while attempting to obtain the benchmark’s answer key.The incident offers a rare opportunity to walk through a real AI attack chain from beginning to end—not just what happened, but what defenders could have done to prevent or detect every stage along the way.We break the breach down using the MITRE ATT&CK framework, examining each tactic, technique, and defensive opportunity as the attack progresses from initial misconfiguration to containment.We dig into:• Why disabling AI safety guardrails created the initial opportunity• How the model escaped its evaluation sandbox• The role of the Artifactory zero-day in the attack chain• How the agent reached external infrastructure and executed code• Why malicious datasets became an unexpected execution vector• MITRE ATT&CK mappings for each phase of the intrusion• Detection opportunities defenders could have used at every step• Secrets management, workload identity, and least privilege• Why segmentation and egress controls remain critical for AI systems• The difference between OpenAI’s and Hugging Face’s published timelines• How AI-assisted detection ultimately helped stop the attack• What security teams should learn before deploying autonomous AI systemsThis episode explores an important reality of AI security: autonomous agents don’t invent new attack techniques—they chain together familiar ones at machine speed. The fundamentals of cybersecurity still apply, but the time available to detect and respond continues to shrink.The takeaway: don’t ask whether your AI system is powerful. Ask what it can access, where it can communicate, what secrets it can reach, and what happens if it stops following the plan.(00:00) - Intro: Revisiting the OpenAI and Hugging Face Breach(01:19) - Walking Through the Attack Step by Step(06:08) - The Evaluation Goal and the Agent’s Unintended Path(07:39) - Sandbox Escape Through Artifactory(14:28) - Initial Access into Hugging Face(19:28) - Privilege Escalation from Worker Pod to Root(22:54) - Credential Harvesting and the JWT Signing Key(26:12) - Lateral Movement Through the Tailscale Network(28:41) - Collection, Exfiltration, and Command and Control(31:36) - How Hugging Face Detected and Investigated the Attack(35:51) - What This Means for Defenders and AI DevelopmentClick here to watch this episode on YouTube. Creators & Guests Derek Banks - HostBronwen Aker - HostBrought to you by:Black Hills Information Security https://www.blackhillsinfosec.com☯️ Introducing BHIS Fusion Penetration Testinghttps://www.blackhillsinfosec.com/fusion-penetration-testing/Antisyphon Traininghttps://www.antisyphontraining.com/Active Countermeasureshttps://www.activecountermeasures.comWild West Hackin Festhttps://wildwesthackinfest.com🔗 Register for FREE Infosec Webcasts, Anti-casts & Summitshttps://poweredbybhis.com Click here to view the episode transcript.
    続きを読む 一部表示
    42 分
  • Agentic Terminology | Episode 64

    Agentic Terminology | Episode 64
    2026/07/31
    In this episode of BHIS Presents: AI Security Ops, the team tackles one of the biggest sources of confusion in modern AI:What’s the difference between prompts, skills, tools, memory, and sub-agents?These terms are everywhere in discussions about agentic AI. They’re often used interchangeably—but they describe very different capabilities. More importantly, each one introduces its own unique security risks.If you’re building, deploying, or securing AI agents, understanding this vocabulary isn’t just helpful. It’s essential.Because every new capability an agent gains is also a new attack surface.We break down each core building block of agentic systems, explain what it actually does, and discuss how attackers can abuse it—from prompt injection and memory poisoning to supply-chain attacks and excessive tool permissions.We dig into:- The difference between prompts, skills, tools, memory, and sub-agents- Why prompts define behavior but don’t create lasting capability- How skills package reusable expertise without granting new permissions- Why tools are what allow AI agents to take real-world actions- The security risks of giving agents excessive privileges- How prompt injection remains the biggest threat facing AI agents today- Why memory transforms a one-time attack into a persistent compromise- How memory poisoning can influence future conversations- Why sub-agents improve scalability while creating new trust boundaries- The dangers of delegation, confused deputies, and poisoned summaries- Why every new capability increases an agent’s attack surface- How applying least privilege dramatically reduces AI security riskThis episode explores one of the most important mental models in agentic AI: think of an AI agent like a new employee.The prompt is the job description.Skills are the documented procedures.Tools are the systems they’re allowed to access.Memory is their notebook.Sub-agents are the coworkers they delegate work to.Every one of those components makes an agent more capable—and every one creates new opportunities for something to go wrong.The takeaway: don’t evaluate an AI agent by how intelligent it is. Evaluate what it can access, what it can change, what it remembers, and who it trusts.—Chapters0:00 – Intro: Understanding Agentic AI Terminology1:18 – Prompts: Instructions and Prompt Injection3:18 – Skills: Reusable Knowledge and Supply Chain Risk5:18 – Tools: Permissions, Actions, and Least Privilege7:40 – Memory: Persistence and Memory Poisoning10:08 – Sub-Agents: Delegation and Trust Chains12:18 – Putting It All Together: Expanding Attack Surface14:05 – Final Takeaways—Key Concepts & TopicsPrompts- System prompts vs. user prompts- Temporary instructions- Prompt injection attacks- Trusted vs. untrusted inputsSkills- Reusable task expertise- On-demand procedural knowledge- Context efficiency- Supply-chain trustTools- External capabilities- Email, web search, databases, and code execution- Permission boundaries- Least privilegeMemory- Persistent context- Long-term personalization- Memory poisoning- Privacy and data protectionSub-Agents- Task delegation- Isolated context windows- Confused deputy attacks- Trust boundariesAgent Security- Expanding attack surface- Capability versus risk- Secure agent design- Defense-in-depth for AI systemsLearn more about Black Hills Information Security:https://www.blackhillsinfosec.com/Check out Antisyphon Training:https://www.antisyphontraining.com/#AISecurity #CyberSecurity #LLMSecurity #ArtificialIntelligence #AgenticAI #AIAgents #PromptInjection #InfoSec #BHIS #Antisyphon(00:00) - Intro: Understanding Agentic AI Terminology(01:28) - Prompts: Instructions and Prompt Injection(07:00) - Skills: Reusable Knowledge and Supply Chain Risk(11:55) - Tools: Permissions, Actions, and Least Privilege(14:50) - Memory: Persistence and Memory Poisoning(22:54) - Sub-Agents: Delegation and Trust Chains(26:52) - Putting It All Together: Expanding Attack Surface(27:58) - Final TakeawaysClick here to watch this episode on YouTube. Creators & Guests Brian Fehrman - HostBronwen Aker - HostDerek Banks - HostBrought to you by:Black Hills Information Security https://www.blackhillsinfosec.com☯️ Introducing BHIS Fusion Penetration Testinghttps://www.blackhillsinfosec.com/fusion-penetration-testing/Antisyphon Traininghttps://www.antisyphontraining.com/Active Countermeasureshttps://www.activecountermeasures.comWild West Hackin Festhttps://wildwesthackinfest.com🔗 Register for FREE Infosec Webcasts, Anti-casts & Summitshttps://poweredbybhis.com Click here to view the episode transcript.
    続きを読む 一部表示
    29 分
  • AI News Stories | Episode 63

    AI News Stories | Episode 63
    2026/07/27
    In this episode of BHIS Presents: AI Security Ops, the team follows a single trend that is changing the economics of cyberattacks:The machine-speed attacker is no longer theoretical.Across four stories from a single week, we watch AI move through every stage of the attack lifecycle. First it writes exploits from public patches. Then it discovers and weaponizes vulnerabilities. Next it helps attackers build phishing infrastructure like a software company. Finally, AI agents begin carrying out ransomware operations with minimal human intervention.Each story stands on its own. Together, they paint a much bigger picture.The window defenders have relied on for decades—the time between disclosure and exploitation—is rapidly disappearing.We dig into:• How Anthropic demonstrated AI-generated exploits in under an hour• Why “N-day” vulnerabilities are becoming “N-hour” attacks• The AI-discovered WordPress wp2shell exploit chain under active attack• The ServiceNow AI Platform vulnerability and rapid weaponization• Why patching alone is no longer enough• How attackers are using generative AI to build phishing campaigns at scale• What Rapid7 uncovered inside a live AI-assisted malware development lab• Why behavioral detection still catches many AI-assisted attacks• JadePuffer and EncForge’s AI-driven ransomware targeting AI infrastructure• The debate around fully autonomous cyberattacks• What security teams should prioritize as attackers move at machine speedThis episode explores a critical shift in cybersecurity: AI is not creating entirely new attack techniques. Instead, it is dramatically compressing the time required to discover vulnerabilities, build exploits, develop tooling, and execute attacks.For defenders, the question is no longer simply “Are we patched?”It is:Can an attacker reach us before we finish patching, and would our controls actually stop them?—Key Concepts & TopicsMachine-Speed Attacks• AI-generated exploit development• Shrinking disclosure-to-exploitation timelines• Why patch windows continue to collapseExploit Development• Reverse engineering security patches• AI-assisted vulnerability research• Practical impacts on defender response timesActive Exploitation• WordPress wp2shell attacks• ServiceNow AI Platform compromise• Post-exploitation persistence and huntingAI-Powered Malware Operations• AI-generated phishing infrastructure• Automated testing and documentation• Scaling attacker operations with LLMsAgentic Ransomware• JadePuffer and EncForge• AI targeting AI infrastructure• Autonomous attack capabilities• Protecting model weights and AI assetsDefensive Strategy• Exposure management• Behavioral detection• Adversarial exposure validation• Protecting AI infrastructure and secrets• Prioritizing reachable risk over severity scores(00:00) - Intro: The Machine-Speed Attacker(01:20) - Story 1: When N-Day Becomes N-Hour(09:13) - Story 2: AI-Discovered WordPress and ServiceNow Exploits(15:59) - Story 3: Inside the AI Malware Factory(17:29) - Story 4: Agentic Ransomware Targets AIClick here to watch this episode on YouTube. Creators & Guests Derek Banks - HostBronwen Aker - HostBrian Fehrman - HostBrought to you by:Black Hills Information Security https://www.blackhillsinfosec.com☯️ Introducing BHIS Fusion Penetration Testinghttps://www.blackhillsinfosec.com/fusion-penetration-testing/Antisyphon Traininghttps://www.antisyphontraining.com/Active Countermeasureshttps://www.activecountermeasures.comWild West Hackin Festhttps://wildwesthackinfest.com🔗 Register for FREE Infosec Webcasts, Anti-casts & Summitshttps://poweredbybhis.com Click here to view the episode transcript.
    続きを読む 一部表示
    23 分
adbl_web_anon_alc_button_suppression_t1
まだレビューはありません