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OpenAI Report Identifies Malicious Use of AI in Cloud-Based Cyber Threats — Campus Technology

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OpenAI Report Identifies Malicious Use of AI in Cloud-Based Cyber Threats

A report from OpenAI identifies the misuse of artificial intelligence in cybercrime, social engineering, and influence operations, particularly those targeting or operating through cloud infrastructure. In “Disrupting Malicious Uses of AI: June 2025,” the company outlines how threat actors are weaponizing large language models for malicious ends — and how OpenAI is pushing back.

The report highlights a growing reliance on AI by adversaries to scale scams, automate phishing and deploy tailored misinformation across platforms like Telegram, TikTok and Facebook. OpenAI says it is countering these threats using its own AI systems alongside human analysts, while coordinating with cloud providers and global security partners to take action against offenders.

In the three months since its previous update, the company says it has detected and disrupted activity including:

  • Cyber operations targeting cloud-based infrastructure and software.
  • Social engineering and scams scaling through AI-assisted content creation.
  • Influence operations attempting to manipulate public discourse using AI-generated posts on platforms like X, TikTok, Telegram and Facebook.

The report details 10 case studies where OpenAI banned user accounts and shared findings with industry partners and authorities to strengthen collective defenses.

Here’s how the company detailed the tactics, techniques, and procedures (TTPs) as presented in the discussion of one representative case — a North Korea-linked job scam operation using ChatGPT to generate fake résumés and spoof interviews:

Activity LLM ATT&CK Framework Category
Automating to systematically fabricate detailed résumés aligned to various tech job descriptions, personas, and industry norms. Threat actors automated generation of consistent work histories, educational backgrounds, and references via looping scripts. LLM Supported Social Engineering
Threat actors utilized the model to answer employment-related, likely application questions, coding assignments, and real-time interview questions, based on particular uploaded resumes. LLM Supported Social Engineering
Threat actors sought guidance for remotely configuring corporate-issued laptops to appear as though domestically located, including advice on geolocation masking and endpoint security evasion methods. LLM-Enhanced Anomaly Detection Evasion
LLM assisted coding of tools to move the mouse automatically, or keep a computer awake remotely, possibly to assist in remote working infrastructure setups. LLM Aided Development

Beyond the employment scam case, OpenAI’s report outlines multiple campaigns involving threat actors abusing AI in cloud-centric and infrastructure-based attacks.

Cloud-Centric Threat Activity

Many of the campaigns OpenAI disrupted either targeted cloud environments or used cloud-based platforms to scale their impact:

  • A Russian-speaking group (Operation ScopeCreep) used ChatGPT to assist in the iterative development of sophisticated Windows malware, distributed via a trojanized gaming tool. The campaign leveraged cloud-based GitHub repositories for malware distribution and used Telegram-based C2 channels.
  • Chinese-linked groups (KEYHOLE PANDA and VIXEN PANDA) used ChatGPT to support AI-driven penetration testing, credential harvesting, network reconnaissance, and automation of social media influence. Their targets included US federal defense industry networks and government communications systems.
  • An operation dubbed Uncle Spam, also linked to China, generated polarizing US political content using AI and pushed it via social media profiles on X and Bluesky.
  • Wrong Number, likely based in Cambodia, used AI-generated multilingual content to run task scams via SMS, WhatsApp, and Telegram, luring victims into cloud-based crypto payment schemes.

    SMS randomly sent to an OpenAI investigator, generated using ChatGPT.
    [Click on image for larger view.] SMS randomly sent to an OpenAI investigator, generated using ChatGPT. (source: OpenAI).

Defensive AI in Action

OpenAI says it is using AI as a “force multiplier” for its investigative teams, enabling it to detect abusive activity at scale. The report also highlights how using AI models can paradoxically expose malicious actors by providing visibility into their workflows.

“AI investigations are an evolving discipline,” the report notes. “Every operation we disrupt gives us a better understanding of how threat actors are trying to abuse our models, and enables us to refine our defenses.”

The company calls for continued collaboration across the industry to strengthen defenses, noting that AI is only one part of the broader internet security ecosystem.

For cloud architects, platform engineers and security professionals, the report is a useful read. It illustrates not only how attackers are using AI to speed up traditional tactics, but also how cloud-based services are central both to their targets and to the infrastructure of modern threat campaigns.

The full report is available on the OpenAI site here.

About the Author



David Ramel is an editor and writer at Converge 360.





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Overcoming Roadblocks to Innovation — Campus Technology

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Register Now for Tech Tactics in Education: Overcoming Roadblocks to Innovation

Tech Tactics in Education will return on Sept. 25 with the conference theme “Overcoming Roadblocks to Innovation.” Registration for the fully virtual event, brought to you by the producers of Campus Technology and THE Journal, is now open.

Offering hands-on learning and interactive discussions on the most critical technology issues and practices across K–12 and higher education, the conference will cover key topics such as:

  • Tapping into the potential of AI in education;
  • Navigating cybersecurity and data privacy concerns;
  • Leadership and change management;
  • Evaluating emerging ed tech choices;
  • Foundational infrastructure for technology innovation;
  • And more.

A full agenda will be announced in the coming weeks.

Call for Speakers Still Open

Tech Tactics in Education seeks higher education and K-12 IT leaders and practitioners, independent consultants, association or nonprofit organization leaders, and others in the field of technology in education to share their expertise and experience at the event. Session proposals are due by Friday, July 11.

For more information, visit TechTacticsInEducation.com.

About the Author



Rhea Kelly is editor in chief for Campus Technology, THE Journal, and Spaces4Learning. She can be reached at [email protected].





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9 AI Ethics Scenarios (and What School Librarians Would Do)

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A common refrain about artificial intelligence in education is that it’s a research tool, and as such, some school librarians are acquiring firsthand experience with its uses and controversies.

Leading a presentation last week at the ISTELive 25 + ASCD annual conference in San Antonio, a trio of librarians parsed appropriate and inappropriate uses of AI in a series of hypothetical scenarios. They broadly recommended that schools have, and clearly articulate, official policies governing AI use and be cautious about inputting copyrighted or private information.

Amanda Hunt, a librarian at Oak Run Middle School in Texas, said their presentation would focus on scenarios because librarians are experiencing so many.


“The reason we did it this way is because these scenarios are coming up,” she said. “Every day I’m hearing some other type of question in regards to AI and how we’re using it in the classroom or in the library.”

  • Scenario 1: A class encourages students to use generative AI for brainstorming, outlining and summarizing articles.

    Elissa Malespina, a teacher librarian at Science Park High School in New Jersey, said she felt this was a valid use, as she has found AI to be helpful for high schoolers who are prone to get overwhelmed by research projects.

    Ashley Cooksey, an assistant professor and school library program director at Arkansas Tech University, disagreed slightly: While she appreciates AI’s ability to outline and brainstorm, she said, she would discourage her students from using it to synthesize summaries.

    “Point one on that is that you’re not using your synthesis and digging deep and reading the article for yourself to pull out the information pertinent to you,” she said. “Point No. 2 — I publish, I write. If you’re in higher ed, you do that. I don’t want someone to put my work into a piece of generative AI and an [LLM] that is then going to use work I worked very, very hard on to train its language learning model.”

  • Scenario 2: A school district buys an AI tool that generates student book reviews for a library website, which saves time and promotes titles but misses key themes or introduces unintended bias.

    All three speakers said this use of AI could certainly be helpful to librarians, but if the reviews are labeled in a way that makes it sound like they were written by students when they weren’t, that wouldn’t be ethical.

  • Scenario 3: An administrator asks a librarian to use AI to generate new curriculum materials and library signage. Do the outputs violate copyright or proper attribution rules?

    Hunt said the answer depends on local and district regulations, but she recommended using Adobe Express because it doesn’t pull from the Internet.

  • Scenario 4: An ed-tech vendor pitches a school library on an AI tool that analyzes circulation data and automatically recommends titles to purchase. It learns from the school’s preferences but often excludes lesser-known topics or authors of certain backgrounds.

    Hunt, Malespina and Cooksey agreed that this would be problematic, especially because entering circulation data could include personally identifiable information, which should never be entered into an AI.

  • Scenario 5: At a school that doesn’t have a clear AI policy, a student uses AI to summarize a research article and gets accused of plagiarism. Who is responsible, and what is the librarian’s role?

    The speakers as well as polled audience members tended to agree the school district would be responsible in this scenario. Without a policy in place, the school will have a harder time establishing whether a student’s behavior constitutes plagiarism.

    Cooksey emphasized the need for ongoing professional development, and Hunt said any districts that don’t have an official AI policy need steady pressure until they draft one.

    “I am the squeaky wheel right now in my district, and I’m going to continue to be annoying about it, but I feel like we need to have something in place,” Hunt said.

  • Scenario 6: Attempting to cause trouble, a student creates a deepfake of a teacher acting inappropriately. Administrators struggle to respond, they have no specific policy in place, and trust is shaken.

    Again, the speakers said this is one more example to illustrate the importance of AI policies as well as AI literacy.

    “We’re getting to this point where we need to be questioning so much of what we see, hear and read,” Hunt said.

  • Scenario 7: A pilot program uses AI to provide instant feedback on student essays, but English language learners consistently get lower scores, leading teachers to worry the AI system can’t recognize code-switching or cultural context.

    In response to this situation, Hunt said it’s important to know whether the parent has given their permission to enter student essays into an AI, and the teacher or librarian should still be reading the essays themselves.

    Malespina and Cooksey both cautioned against relying on AI plagiarism detection tools.

    “None of these tools can do a good enough job, and they are biased toward [English language learners],” Malespina said.

  • Scenario 8: A school-approved AI system flags students who haven’t checked out any books recently, tracks their reading speed and completion patterns, and recommends interventions.

    Malespina said she doesn’t want an AI tool tracking students in that much detail, and Cooksey pointed out that reading speed and completion patterns aren’t reliably indicative of anything that teachers need to know about students.

  • Scenario 9: An AI tool translates texts, reads books aloud and simplifies complex texts for students with individualized education programs, but it doesn’t always translate nuance or tone.

    Hunt said she sees benefit in this kind of application for students who need extra support, but she said the loss of tone could be an issue, and it raises questions about infringing on audiobook copyright laws.

    Cooksey expounded upon that.

    “Additionally, copyright goes beyond the printed work. … That copyright owner also owns the presentation rights, the audio rights and anything like that,” she said. “So if they’re putting something into a generative AI tool that reads the PDF, that is technically a violation of copyright in that moment, because there are available tools for audio versions of books for this reason, and they’re widely available. Sora is great, and it’s free for educators. … But when you’re talking about taking something that belongs to someone else and generating a brand-new copied product of that, that’s not fair use.”

Andrew Westrope is managing editor of the Center for Digital Education. Before that, he was a staff writer for Government Technology, and previously was a reporter and editor at community newspapers. He has a bachelor’s degree in physiology from Michigan State University and lives in Northern California.





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Bret Harte Superintendent Named To State Boards On School Finance And AI

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Bret Harte Superintendent Named To State Boards On School Finance And AI – myMotherLode.com

































































 




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