The new film about an FBI agent chasing a white supremacist terror cell is based on a true story—and one that connects the headlines of 30 years ago to those of today.

In _The Order,_ director Justin Kurzel’s electric new film, Terry Husk, a haggard, possessed FBI veteran played by Jude Law, pores over a thin paperback with a blood-red cover, paging through diagrams of targeted killings, bombings, and a gallows erected in front of the United States Capitol.

“There are six steps in that book,” says a young sheriff deputized as his assistant, played by Tye Sheridan. He gives the Cliff Notes version as he scours the book, his eyes riveted.

“Recruiting,” he says. “Fundraising. Armed revolution. Domestic terror. Assassination.

“Number six is the day of the rope.”

The book is _The Turner Diaries_, a 1978 novel that depicts the violent overthrow of the American government by armed white supremacist insurgents and the extermination of people of color and Jews in a race war. Photocopied pages from it were found in Oklahoma City bomber Timothy McVeigh’s getaway car when he was apprehended by law enforcement.

Along with Husk and Bob Mathews—the founder of a murderous underground white supremacist guerrilla outfit that counterfeited money and robbed banks and armored cars, played by Nicholas Hoult—_The Turner Diaries_ is the third major character in _The Order_. Though Mathews formally named his group the Silent Brotherhood and claimed he took little inspiration from William Luther Pierce’s incendiary novel, he and his comrades did refer to their group as “The Order”—the same term used in the book for the protagonist’s genocidal militants.

The book’s crimson cover and lurid drawings resurface time and time again. Mathews reads excerpts to his young son before bedtime; a pastor at a neo-Nazi compound in Idaho proffers it to visiting law enforcement agents; and it turns up in the hands of FBI agents desperately seeking to plot out the insurgents’ next moves.

_The Order_ unearths a critical chapter in the history of the American extreme right largely forgotten by the general public. The murder of Jewish talk radio host Alan Berg in 1984 by two of Mathews’ acolytes brought the Order to national attention 30 years ago and inspired not one but two Hollywood films in that decade—_Betrayed_ and Oliver Stone’s _Talk Radio_. Since then, though, only close observers of prison gang and skinhead culture have had cause to track mentions of the Silent Brotherhood by tweaked-out Aryan Brotherhood killers or the annual “Martyrs Day” pilgrimage of Hammerskins from across the West Coast to Whidbey Island in the Puget Sound, where Mathews met his fiery death during a shootout with the FBI.

Now, as the country ponders a return to the 2016-2020 period, when Mathews’ ideological offspring ran riot from Oregon to Washington, DC, his saga is getting marquee billing.

While the film debuts almost a full decade into the American extreme right’s current revival, screenwriter Zach Baylin and producer Bryan Haas began developing the project back in 2016, before the deadly 2017 Unite the Right rally in Charlottesville, Virginia. Baylin tells WIRED that he and Haas stumbled on _The Turner Diaries_ while researching Ruby Ridge, the 1990s militia movement, and McVeigh (who slept with the book under his pillow) and casting around for a lesser-known story to explore the origins of American extremism.

“We were looking to encase the story of one of these groups inside a classic crime thriller,” Baylin says. They stumbled across _The Silent Brotherhood_, a 1989 book by reporters Kevin Flynn and Gary Gerhardt that traced the entire arc of Mathews’ crime spree, from his teenage radicalization through the John Birch Society and Phoenix militias all the way through his death and the subsequent criminal trials of his followers.

“The crimes the Order committed and the way the investigation unfolded, it had the framework of the kind of film that we’d been talking about,” he said.

Flynn and Gerhart’s book, which began with their coverage of Berg’s assassination in his driveway and followed the Order’s saga through the federal pursuit, investigation, and prosecution, is remarkably detailed. Once members of the group were up for trial, Flynn and Gerhart spent hours interviewing them in the Arapahoe County jail, gathering priceless material that allowed them to reconstruct the terrorist group’s inner workings in minute detail. Readers of the book, which is back in print (with a new title) after three decades off the shelves, will note the film’s fidelity to life, particularly in the robbery and heist scenes. However, for Flynn and Gerhardt—who died in 2015—the minutiae of Mathews’ terror campaign were a mechanism to engage audiences with a deeper, darker reality.

“We didn’t write the book for the details. We wrote it to expose the banality of evil, so readers could understand where these folks come from and how endemic it is in American society,” says Flynn, who reported for the Rocky Mountain News for nearly three decades before it shuttered in 2009. Since 2015, he has served as a city councilman in Denver.

_The Order_ is the sort of film America does not produce anymore. Its taut action scenes hearken back to _Heat_, _To Live and Die in L.A._, _The French Connection_, and Sidney Lumet’s police corruption canon (_Serpico_, _Prince of the City_, _Q&A_); the droning soundtrack does not overwhelm viewers; and Adam Arkapaw’s washed-out cinematography encapsulates both the grandeur and the intimidating solitude of the interior Pacific Northwest. The dialog is sparing, direct, and—in spite of Mathews’ grandiose promises of a renewed whites-only bastion in the Pacific Northwest—remarkably free of proselytizing.

For a movie shot in such wide-open landscapes, _The Order_ is tinged through with claustrophobia, a testament to the tension rife throughout Baylin’s writing and Kurzel’s meticulous direction. Like Al Pacino and Robert DeNiro in Michael Mann’s _Heat_, Hoult and Law only come face to face with each other a few times before their penultimate confrontation. However, Kurzel had both actors follow each other for a day and compile dossiers on their opposite number to develop a granular sense of how a manhunt actually functions.

“I wanted them to ask themselves, what does that feel like having a relationship with someone you’re trying to take down? You’re living with a phantom, in a way,” Kurzel says.

Law, whose slow-burn performance is unlike any prior role from his four decades on stage and screen, says the similarities between Husk and Mathews as two opposites of the same coin are at the core of _The Order_’s dramatic tension.

“They’re more alike than they’d ever admit—both are driven, charismatic, and know exactly how to manipulate those around them to achieve their goals,” he says. “Nicholas and I really leaned into that symmetry during our scenes together. It’s almost like they’re looking into a dark mirror—each recognizing qualities in the other that they either admire or fear. That underlying connection adds layers to their conflict, making it not just a clash of ideologies but also a deeply personal battle. It was fascinating to explore that tension with Nicholas.”

Mathews’ brief campaign of armed insurgency and domestic terrorism has continued to inspire generations of extremists in the United States and beyond, from McVeigh and the neo-Nazi bankrollers of the Aryan Republican Army to the killers of Germany’s National Socialist Underground, all the way through to contemporary groups like Atomwaffen Division, the Base and the Terrorgram Collective. The latter group, which federal law enforcement believes to be a “bold-letter, category one” domestic terrorism threat, circulates voluminous propaganda booklets that meld the ethos of _The Turner Diaries_ with Ted Kaczynski’s anti-industrial-civilization ethos and neo-Nazi occultism.

Terrorgram’s materials, which include viable bomb-making instructions, camouflage and tactical guides, and instructions on how to disable critical infrastructure like electrical substations, water treatment plants and dams, have radicalized at least one so-called “saint,” or mass shooter, and are alleged to have been connected to a series of power grid attacks in North Carolina as well as several active federal prosecutions.

“William Pierce doesn’t build bombs,” Mark Potok of the Southern Poverty Law Center, told Rolling Stone a quarter of a century ago. “He builds bombers.” In many ways, the Terrorgram Collective fulfills the same role now, and its publications have become the modern-day version of the _Turner Diaries_. Disseminated worldwide through the moderation-free wilderness of Telegram, the group’s message of hate and violence is now circulating independently of any organized group or ideology for disaffected, unbalanced “lone wolves” to latch onto as justification for future atrocities.

While _The Order_ remains firmly rooted in the past save for one passing reference to the 1995 Oklahoma City bombing in a title card, during production there was no escaping the drumbeat of resurgent far-right militancy in the United States. Kurzel, the director, recalls watching news coverage of the January 6 insurrection and remarking on the gallows erected outside the Capitol building—a drawing of which features in the book and the exposition scene with law. “_The Turner Diaries_ started to become more visible in a present-day setting in a way I was kind of shocked by,” he says, speaking to WIRED from his Tasmania residence. Indeed, following January 6, Amazon removed _The Turner Diaries_ from its online inventory.

Hoult’s bravura portrayal of an ice-cool, controlled yet menacing Mathews through the Order’s campaign of armed robbery, counterfeiting, murder, and armed confrontation with the FBI is one of the film’s dual anchors. Aside from a striking physical resemblance to the Silent Brotherhood’s founder, Hoult closely studied his subject, aping Mathews’ mannerisms and movements from old documentary footage, studying texts that radicalized his subject, lifting weights, and cutting alcohol from his diet.

“Mathews was someone who thought and planned so in advance of what his ultimate goal was, I think he always kept in sight. That’s something Justin and I spoke about, that he wouldn’t lose his head on trivial things or things that would potentially harm his cause. In his mind, he’d already, in some ways, planned his destiny,” Hoult tells WIRED.

By choosing to play Mathews with reserve instead of bombast, as more of a watcher who carefully observes his surroundings and other people to better understand how to turn situations to his advantage, Hoult aimed to show audiences how someone with the charisma of his villain could attract followers and build a movement.

“I think that shows how they penetrate communities and societies in a different way, and perhaps people in the future might be less susceptible to people who behave like him,” he says.

As with any artistic project that focuses on extremism and mass violence, _The Order_’s production team walked a fine line between showing Mathews’ magnetism and the murderous project at the heart of his ideology and actions.

“I think you need to understand the pull of a figure like this,” says Kurzel, whose prior films _Snowtown_ and _Nitram_ depicted, respectively, youthful serial killers and Australia’s worst mass shooting, the 1996 Port Arthur massacre. “Mathews is definitely someone who understands their reach and how to communicate and gather people. There’s gonna be a certain kind of charisma about that.”

Haas, one of the film’s producers, echoed Kurzel's remarks about art pushing the boundaries of acceptability. “It felt like part of the movie was to show the appeal of Bob. He was someone who had charisma, and that tied to these really toxic ideas is really dangerous,” Haas says, praising the “unrelenting realism” the cast brought to their performances.

Ultimately, the hope of slipping an unsparing portrayal of domestic extremism—produced outside of the Hollywood studio system—into the December award season is to reintroduce a discussion of radicalization to American society. “If you don’t learn from history, you’re doomed to repeat it—how a guy that, in the way Nick depicted him, could live down anybody’s street,” says Haas. “There are lots of people right now who are hurting and struggling and looking for answers.”

_Updated: 12/6/2024 4:01 pm EST: This story was updated to clarify which character reads out six steps given in_ The Turner Diaries.

The Real Story of “The Order”

Cybersecurity researchers have disclosed multiple security flaws impacting open-source machine learning (ML) tools and frameworks such as MLflow, H2O, PyTorch, and MLeap that could pave the way for code execution.
The vulnerabilities, discovered by JFrog, are part of a broader collection of 22 security shortcomings the supply chain security company first disclosed last month.
Unlike the first

Researchers Uncover Flaws in Popular Open-Source Machine Learning Frameworks

We are excited to introduce LLMail-Inject, a new challenge focused on evaluating state-of-the-art prompt injection defenses in a realistic simulated LLM-integrated email client. In this challenge, participants assume the role of an attacker who sends an email to a user. The user then queries the LLMail service with a question (e.

  

We are excited to introduce LLMail-Inject, a new challenge focused on evaluating state-of-the-art prompt injection defenses in a realistic simulated LLM-integrated email client. In this challenge, participants assume the role of an attacker who sends an email to a user. The user then queries the LLMail service with a question (e.g., “please summarize the last emails about project X”), which prompts the retrieval of relevant emails from a simulated email database. The inclusion of the attacker’s email in these retrievals varies depending on the scenario. The LLMail service is equipped with tools, and the attacker’s objective is to manipulate the LLM into executing a specific tool call as defined by the challenge design, while bypassing the prompt injection defenses in place. The challenge contains several scenarios that require the attacker to ensure that their email is retrieved by the client under certain conditions. Teams with the highest scores will win awards from a total pool of $10,000 USD. 

Since this challenge takes place in a simulated environment, submissions will not be part of Microsoft’s Zero Day Quest. However, since this is a realistic environment, the prompt injection techniques you develop might be applicable to real systems. We encourage you to apply your learnings from this challenge and participate in the Zero Day Quest!  

**What are Prompt Injection Attacks (PIA)?**

In prompt injection attacks against large language models (LLMs), an attacker crafts a specific input (prompt) designed to manipulate the behavior of the model in unintended ways. In such attacks, the attacker exploits the model’s ability to follow instructions embedded within text inputs. By embedding possibly malicious instructions within the input data, the attacker aims to bypass the model’s intended functionality, often to execute unauthorized commands, leak sensitive information, or manipulate outputs. Understanding and defending against prompt injection attacks is crucial for maintaining the security and reliability of LLM-based systems. 

**How does PIA work?**

Prompt injection attacks work by exploiting the inherent design of LLMs, which are trained to follow instructions and generate coherent and contextually appropriate responses based on the input they receive. Attackers craft inputs that include injected commands, which the model then interprets and executes as part of its response generation process. These commands can be embedded in various ways, such as through straight-forward instructions, cleverly phrased questions, statements, or code snippets that the model processes without recognizing them as injected instructions. For instance, an attacker might insert a command within a seemingly benign email message that tricks the model into performing actions like unauthorized data access or executing specific functions. The success of these attacks hinges on the model’s lack of context about the legitimacy of the instructions embedded in the input, making it crucial for developers to implement robust defenses and validation mechanisms to detect and mitigate such manipulative inputs. 

**What are the challenge scenarios and levels in LLMail-Inject?**

The LLMail-Inject challenge is structured into various scenarios based on retrieval configurations and the attacker’s objectives, resulting in a total of 40 levels. Each level is a unique combination of Retrieval-Augmented Generation (RAG) configuration, an LLM (GPT-4o mini or Phi-3-medium-128k-instruct), and a specific defense mechanism. 

Each level and scenario in LLMail-Inject tests different aspects of the LLM’s ability to withstand prompt injection attacks and aims to highlight the importance of robust defense mechanisms. 

**What defenses are included in LLMail-Inject?**

Despite prompt injection attacks being relatively new, researchers have already proposed several defenses to mitigate their effect. The LLMail-Inject challenge incorporates various state-of-the-art defenses to test the robustness of LLMs against prompt injection attacks. These include: 

*   Spotlighting \[1\]: A preventative defense that “marks” data (as opposed to instructions) that is provided to an LLM using methods like adding special delimiters, encoding data (e.g., in base64), or marking each token in the data with a special preceding token. 
    
*   PromptShield \[2\]: A black-box classifier designed to detect prompt injections, ensuring that malicious prompts are identified and mitigated. 
    
*   LLM-as-a-judge: This defense uses an LLM to detect attacks by evaluating prompts instead of relying on a trained classifier. 
    
*   TaskTracker \[3\]: Based on analyzing the model’s internal states to detect task drift, this defense extracts activations when the user first prompts the LLM and again when the LLM processes external data. It then contrasts these activation sets to detect drift via a linear probe on the activation deltas. 
    
*   Combination of all: A variant in the challenge where multiple defenses are stacked together, requiring an attack to evade all defenses simultaneously with a single prompt. 
    

**How do I participate?**

To participate in the LLMail-Inject challenge, please follow the instructions below and visit the official challenge website at LLMail-Inject.  

1.  Create a team by signing in with your GitHub account.  
    
2.  Start playing! You can make a submission through the website UI or programmatically via our competition API. 
    

If using the API for programmatic submissions: 

*   We have API documentation on the website and your API key is already injected into the example Python client. 
    
*   Your API key is also available on your user profile page. 
    
*   We have rate limits in place to ensure a great experience for all participants. The website also provides comprehensive information on how to get started, including how to configure your environment and submit your entries. This setup ensures that participants can easily join the competition and contribute, regardless of their level of experience or preferred method of interaction. 
    

**Scoring, winners, and awards**

The Contest starts at 11:00 a.m. Coordinated Universal Time (UTC) on December 9, 2024, and ends at 11:59 a.m. UTC on January 20, 2025 (“Entry Period”). If at least 10% of the levels have not been solved by at least four (4) teams on the end date listed above, we may opt to extend the challenge. Check LLMail-Inject for any updates to the schedule. 

Throughout the event, a live scoreboard will be displayed (here along with the scoring details). The challenge has a total prize pool of $10,000 USD, with awards distributed as follows:  

*   $4,000 USD for the top team 
    
*   $3,000 USD for the second-place team 
    
*   $2,000 USD for the third-place team 
    
*   $1,000 USD for the fourth-place team.  
    

The winning teams will be invited to co-present with the organizers at the IEEE Conference on Secure and Trustworthy Machine Learning (SaTML) 2025.  

**References**

\[1\] Keegan Hines et al. Defending Against Indirect Prompt Injection Attacks With Spotlighting 

\[2\] Azure AI announces Prompt Shields for Jailbreak and Indirect prompt injection attacks 

\[3\] Sahar Abdelnabi et al. Are you still on track!? Catching LLM Task Drift with Activations 

_This challenge is co-organized by Aideen Fay\*, Sahar Abdelnabi\*, Benjamin Pannell\*, Giovanni Cherubin\*, Ahmed Salem, Andrew Paverd, Conor Mac Amhlaoibh, Joshua Rakita, Santiago Zanella-Beguelin, Egor Zverev, Mark Russinovich, and Javier Rando_

(\*: Core contributors).

Announcing the Adaptive Prompt Injection Challenge (LLMail-Inject) 

Researchers testing generative AI systems can use prompt injection, re-register after being banned, and bypass rate limits without running afoul of copyright law.

Source: Vitalii Vodolazskyi via Shutterstock

In a net positive for researchers testing the security and safety of AI systems and models, the US Library of Congress ruled that certain types of offensive activities — such as prompt injection and bypassing rate limits — do not violate the Digital Millennium Copyright Act (DMCA), a law used in the past by software companies to push back against unwanted security research.

The Library of Congress, however, declined to create an exemption for security researchers under the fair use provisions of the law, arguing that an exemption would not be enough to provide security researchers safe haven.

Overall, the triennial update to the legal framework around digital copyright works in the security researchers' favor, as does having clearer guidelines on what is permitted, says Casey Ellis, founder and adviser to crowdsourced penetration testing service BugCrowd.

"Clarification around this type of thing — and just making sure that security researchers are operating in as favorable and as clear an environment as possible — that's an important thing to maintain, regardless of the technology," he says. "Otherwise, you end up in a position where the folks who own the \[large language models\], or the folks that deploy them, they're the ones that end up with all the power to basically control whether or not security research is happening in the first place, and that nets out to a bad security outcome for the user."

Security researchers have increasingly gained hard-won protections against prosecution and lawsuits for conducting legitimate research. In 2022, for example, the US Department of Justice stated that its prosecutors would not charge security researchers with violating the Computer Fraud and Abuse Act (CFAA) if they did not cause harm and pursued the research in good faith. Companies that sue researchers are regularly shamed, and groups such as the Security Legal Research Fund and the Hacking Policy Council provide additional resources and defenses to security researchers pressured by large companies.

In a post to its site, the Center for Cybersecurity Policy and Law called the clarifications by the US Copyright Office "a partial win" for security researchers — providing more clarity but not safe harbor. The Copyright Office is organized under the Library of Congress's purview.

"The gap in legal protection for AI research was confirmed by law enforcement and regulatory agencies such as the Copyright Office and the Department of Justice, yet good faith AI research continues to lack a clear legal safe harbor," the group stated. "Other AI trustworthiness research techniques may still risk liability under DMCA Section 1201, as well as other anti-hacking laws such as the Computer Fraud and Abuse Act."

**Brave New Legal World**

The fast adoption of generative AI systems and algorithms based on big data have become a major disruptor in the information-technology sector. Given that many large language models (LLMs) are based on mass ingestion of copyrighted information, the legal framework for AI systems started off on a weak footing.

For researchers, past experience provides chilling examples of what could go wrong, says BugCrowd's Ellis.

"Given the fact that it's such a new space — and some of the boundaries are a lot fuzzier than they are in traditional IT — a lack of clarity basically always converts to a chilling effect," he says. "For folks that are mindful of this, and a lot of security researchers are pretty mindful of making sure they don't break the law as they do their work, it has resulted in a bunch of questions coming out of the community."

The Center for Cybersecurity Policy and Law and the Hacking Policy Council proposed that red teaming and penetration testing for the purpose of testing AI security and safety be exempted from the DMCA, but the Librarian of Congress recommended denying the proposed exemption.

The Copyright Office "acknowledges the importance of AI trustworthiness research as a policy matter and notes that Congress and other agencies may be best positioned to act on this emerging issue," the Register entry stated, adding that "the adverse effects identified by proponents arise from third-party control of online platforms rather than the operation of section 1201, so that an exemption would not ameliorate their concerns."

**No Going Back**

With major companies investing massive sums in training the next AI models, security researchers could find themselves targeted by some pretty deep pockets. Luckily, the security community has established fairly well-defined practices for handling vulnerabilities, says BugCrowd's Ellis.

"The idea of security research being being a good thing — that's now kind of common enough ... so that the first instinct of folks deploying a new technology is not to have a massive blow up in the same way we have in the past," he says. "Cease and desist letters and \[other communications\] that have gone back and forth a lot more quietly, and the volume has been kind of fairly low."

In many ways, penetration testers and red teams are focused on the wrong problems. The biggest challenge right now is overcoming the hype and disinformation about AI capabilities and safety, says Gary McGraw, founder of the Berryville Institute of Machine Learning (BIML), and a software security specialist. Red teaming aims to find problems, not be a proactive approach to security, he says.

"As designed today, ML systems have flaws that can be exposed by hacking but not fixed by hacking," he says.

Companies should be focused on finding ways to produce LLMs that do not fail in presenting facts — that is, "hallucinate" — or are vulnerable to prompt injection, says McGraw.

"We are not going to red team or pen test our way to AI trustworthiness — the real way to secure ML is at the design level with a strong focus on training data, representation, and evaluation," he says. "Pen testing has high sex appeal but limited effectiveness."

**About the Author**

Veteran technology journalist of more than 20 years. Former research engineer. Written for more than two dozen publications, including CNET News.com, Dark Reading, MIT's Technology Review, Popular Science, and Wired News. Five awards for journalism, including Best Deadline Journalism (Online) in 2003 for coverage of the Blaster worm. Crunches numbers on various trends using Python and R. Recent reports include analyses of the shortage in cybersecurity workers and annual vulnerability trends.

Library of Congress Offers AI Legal Guidance to Researchers

A single barrier prevented attackers from exploiting a critical vulnerability in an enterprise collaboration platform. Now there's a workaround.

Source: Kristoffer Tripplaar via Alamy Stock Photo

Two new vulnerabilities in Mitel's MiCollab unified communications and collaboration (UCC) platform could help expose gobs of enterprise data.

MiCollab is a cross-platform application on mobile devices and desktops that combines instant messaging, SMS, phone calls, video calls, file sharing, remote desktop sharing — really any form of collaboration that occurs within an organization, save talking out loud. Organizations rely on it heavily for day-to-day business operations and, invariably, to house large amounts of personal and communications data.

That's what made CVE-2024-35286 so inconvenient when it was discovered earlier this year. This SQL injection vulnerability, resulting from a lack of user input sanitization, earned a "critical" 9.8 score in the Common Vulnerability Scoring System (CVSS) for how it allowed attackers to access important business data, and execute database and management operations at will. It came with a catch, though: A specific configuration was required to reach the vulnerable endpoint, where the treasure lay.

In a new blog post, researchers from watchTowr noted that "No sensible admin would do this" — referring to the undisclosed configuration — so the risk to reliable organizations was low. However, the researchers went on to discover a path traversal vulnerability in MiCollab — not to mention a third, arbitrary file-read vulnerability — which rendered that one lone defense moot.

**The New MiCollab Exploit Chain**

At Black Hat six years ago, a researcher going by the moniker Orange Tsai presented research exposing issues with how Web applications handle path normalization. Using special characters in URLs, attackers could trick Web servers into giving them access to files and directories they shouldn't be able to access.

Researchers from watchTowr put this logic to the test while toying with CVE-2024-35286. Working with an Apache configuration for MiCollab published to the Web back in 2009, they discovered that they could use the input "..;/" to bypass all roadblocks on the way to the vulnerable endpoint — "/npm-admin" from the NuPoint Unified Messaging (UM) component of the platform — with no authentication required. This stacked vulnerability was acknowledged as CVE-2024-41713, and given a "high" CVSS score of 7.5.

CVE-2024-41713 gave new life to the older CVE-2024-35286, and then the researchers discovered yet another zero-day allowing for arbitrary file read, which hasn't been assigned a CVE label or CVSS score. The three work best in combination: CVE-2024-41713 lubricating initial access, the arbitrary file-read issue providing visibility into files across the system, and CVE-2024-35286 enabling any number of malicious operations thereon. For its part, watchTowr published a proof-of-concept (PoC) exploit to GitHub that combines the first two.

"Based on public sources, there are over 10,000 publicly exposed Mitel MiCollab devices," notes Mayuresh Dani, manager of security research at the Qualys Threat Research Unit. "Provided that NuPoint Unified Messaging (NPM) is enabled, a remote threat actor can use CVE-2024-41713 and the \[file-read\] zero-day to access arbitrary files on affected devices."

Which is exactly what the proof-of-concept code does, he adds. "It does so by accessing the npm-pwg directory and invoking the Reconcile Wizard, which is normally used to generate system reports. If the attacker gets ahold of sensitive files containing authentication information on the device, this could be used to gain access to the device and possibly snoop on conversations flowing through the vulnerable instance."

**Hacking Enterprise Communications**

An email arrives in an employee's inbox from their boss. "Hi, please wire a payment to our contractor at \[bank account number\] immediately." The number one thing employees are told, to screen scams like this, is to call their boss to confirm the legitimacy of the email. But what if their phone system itself is breached?

"The vulnerabilities in Mitel MiCollab highlight a growing trend of attackers targeting communication platforms to gain access to sensitive systems," says Callie Guenther, senior manager of cyber threat research at Critical Start. Besides intercepting or blocking an organization's central lines of communication, snooping on employees, or simply causing a general havoc, attackers can also use a platform like MiCollab to facilitate any number of other kinds of cyberattacks. "Similar issues have been exploited in the past, such as the 2022 Mitel MiVoice Connect vulnerability (CVE-2022-29499), which ransomware groups used to deploy Web shells and move laterally through networks," she notes.

Both named CVEs have been patched as of Oct. 9. Mitel acknowledged the arbitrary file-read bug, but hasn't yet patched it at the time of publication. Organizations with MiCollab up to date are covered most of the way, though, as this last issue requires authentication to exploit.

**About the Author**

Nate Nelson is a freelance writer based in New York City. Formerly a reporter at Threatpost, he contributes to a number of cybersecurity blogs and podcasts. He writes "Malicious Life" -- an award-winning Top 20 tech podcast on Apple and Spotify -- and hosts every other episode, featuring interviews with leading voices in security. He also co-hosts "The Industrial Security Podcast," the most popular show in its field.

Bypass Bug Revives Critical N-Day in Mitel MiCollab

AI-powered tools are making cybersecurity tasks easier to solve, as well as easier for the team to handle.

Security professionals say adding large language model (LLM) and generative artificial intelligence (GenAI) capabilities to security programs improves efficiency in threat detection and increases productivity of analysts, according to Dark Reading's latest research on enterprise security. Efficiency and effectiveness were recurring themes.

In Dark Reading's Artificial Intelligence and Machine Learning in Cybersecurity Survey, the top three benefits of using GenAI and LLMs in a cybersecurity program were more efficient threat detection (28%), improved analyst productivity and efficiency (27%), and better threat intelligence analysis (23%).

The promise of AI tools is enhancing the analysts' performance. Almost one-fifth (19%) of respondents said they appreciated how AI helped generate reports faster, while the same number (19%) liked how AI-infused technologies learn and adapt from new information. Fifteen percent felt the pressure lift from AI's ability to analyze security alerts to reduce false positives, while another 15% appreciated how the technology helped them discover and reduce misconfigurations.

Cybersecurity practitioners also saw value in active uses for AI, such as proactive threat hunting (16%), greater user behavior analysis (15%), improved incident response (15%), and a better security posture (11%).

There are also benefits to the business side. LLM tools can optimize resources (13%) to help make an organization's network more efficient and reduce costs (9%). Respondents also see ways GenAI can scale up their operations (12%), as well as improve cybersecurity response by supplementing the skills of the current team (12%). On the budgeting side, LLM use can reduce both the need for additional headcount (11%) and costs of operation (9%).

For more on the impact of AI and ML on cybersecurity, download the Dark Reading report "The State of Artificial Intelligence and Machine Learning in Cybersecurity."

**About the Author**

Karen joined Dark Reading in January 2022 as features editor. She's been in tech editing since before the img tag was introduced, working for outlets such as the IEEE Computer Society, CNET Download.com, and TechTV. She lives in Los Angeles with her husband, son, and two cats. Find her on Mastodon.

LLMs Raise Efficiency, Productivity of Cybersecurity Teams

Ever wonder what an extroverted strategy security nerd does? Wonder no longer! This week, Joe pontificates on his journey at Talos, and then is inspired by the people he gets to meet and help.

Thursday, December 5, 2024 14:02

Welcome to this week’s edition of the Threat Source newsletter. 

I am unbelievably lucky to do the work that I do. My title is technically ‘Senior Security Strategist’. It’s a very fancy title, but basically: I get to research threats with my colleagues and friends to keep people safe here at Talos. I also get to travel and talk to our customers and communities about that work and how we fight that good fight. This has taken me to some interesting places - from Ukraine to California and lots of places in between. Not bad for a guy from a small town in Alabama.  

This gig isn’t for everyone. You must have some extroverted tendencies, and as the youth would say, some ‘rizz’. It’s not enough to talk about something like, say, ransomware. You need to be able to explain it in high technical detail if needed and then explain it to a board of C-levels and speak the language of business they understand. And you need to do it in an engaging way to keep your audiences bought in. It’s a unique blend of security practitioner expertise and the ability to communicate that to audiences, some technical, some not.  

If you’re thinking this also requires some kind of social media influencer level of Hemsworth caliber good looks and hyper charisma, have no fear. I’m about as much a security influencer as Chris Farley was a Beverly Hills ninja. I am just a security nerd who likes to talk. Like I said - I'm very lucky.  

Sometimes this gig takes you to very unexpected places. A couple of weeks ago I found myself at the Ford Foundation Center for Social Justice. I was there to attend and support the NGO-ISAC annual summit. The NGO-ISAC ‘is a non-profit organization improving the cybersecurity of US-based nonprofits.’ They do amazing work supporting cyber security for non-governmental organizations that help protect and promote civil society. We’re also fortunate at Talos to be a partner with them and donate time and resources to support their mission of helping the helpers.  

We are proud to be partners and volunteer our time with NGO-ISAC and it’s members. If you ever want to be truly humbled, spend time with an NGO and learn about what they do. The energy and heart those people have is incredible and will inspire you. They help feed the hungry, cloth the homeless, protect refugees, promote democracies, and generally help take care of some of the most vulnerable people and institutions our society relies upon. They also traditionally struggle with cybersecurity - security investments and practitioner expertise can be difficult to obtain when your budgets are built upon donations to support your mission. They are the embodiment of fighting the good fight, and we at Talos will always have the time to help them help others.  

While I was there, we debuted a custom NGO version of Backdoors & Breaches I helped co-develop with the NGO-ISAC. It was a real hit, and we ran demo games that resonated very well with the audiences. Helping teach cybersecurity to NGOs is fantastic. If we can help them stay secure, there’s so many others who will be helped by it. Also, keep your eyes peeled for a blog post in January about how we designed and created a custom expansion for Backdoors & Breaches.  

Also, the Ford Foundation? Amazing building. It’s in the heart of NYC and is an island of pure serenity. They have an indoor atrium/park that is next level. They pipe in some absolute jazz bangers throughout the entire building that, mixed with the decor, exudes a class I've rarely encountered in my travels. If I could make a blanket out of that entire vibe and wrap myself up in it, I'd do it.  

**The one big thing **

QR Codes, am I right? Sometimes you can scan one with your phone and maybe win a free cheeseburger, sometimes it can take you to a fake O365 phishing site. The tricky bit with QR codes in e-mails is how easily they can avoid spam filters. My man Jaeson Schultz did some great research on attacks, prevalence, and detection of QR codes in e-mail messages. The parts on AI-generated QR imagery are fantastic – be careful what you scan! 

**Why do I care? **

E-mail phishing and evading defenses are a tried and tested tactic with attackers. QR codes are another method of attack, and because they can be difficult to defang/detect, defenders have to work extra hard to understand those threats and stop them.  

**So now what? **

Exercise serious caution when scanning a QR code. If possible, detonate those suspicious QR code e-mails in a sandbox, like Threat Grid. 

**Top security headlines of the week **

At least 97 major water systems in the US have serious cybersecurity vulnerabilities and compliance issues, raising concerns that cyberattacks could disrupt businesses, industry, and the lives of millions of citizens. (Dark Reading) 

The NSA updated its mobile devices security best practices report. Reboot those phones at least once a week friends.  (ZDNet) 

The United States and other Western nations released guidance Tuesday designed to evict the China-linked group in the wake of the high-profile hack. (CyberScoop) 

**Can’t get enough Talos? **

*   New PXA Stealer targets government and education sectors for sensitive information 
*   The TTP Episode 7: Explore this year's Macro-ATT&CK findings  
*   Beers with Talos is back (kind of) with a special “B Team” episode: Misadventures, Rabbit Holes, and Turkey Lurkey Goes to the Movies 

**Upcoming events where you can find Talos ****AVAR (Dec. 4-6)   **

_Chennai, India_    

Vanja Svancer and Chetan Raghuprasad from Cisco Talos will both present, Vanja will be discussing Exploring Vulnerable Windows Drivers, while Chetan presents Sweet and Spicy Recipes for Government Agencies by SneakyChef.   

**Most prevalent malware files from Talos telemetry over the past week  ****SHA 256: 0e2263d4f239a5c39960ffa6b6b688faa7fc3075e130fe0d4599d5b95ef20647 **

MD5: bbcf7a68f4164a9f5f5cb2d9f30d9790 

VirusTotal: https://www.virustotal.com/gui/file/0e2263d4f239a5c39960ffa6b6b688faa7fc3075e130fe0d4599d5b95ef20647/details 

Typical Filename: cwjhtmbwgyomzrhbo.exe 

Claimed Product: n/a 

Detection Name: Win.Dropper.Scar::1201  

**SHA 256: 47ecaab5cd6b26fe18d9759a9392bce81ba379817c53a3a468fe9060a076f8ca **

MD5: 71fea034b422e4a17ebb06022532fdde 

VirusTotal: https://www.virustotal.com/gui/file/9f1f11a708d393e0a4109ae189bc64f1f3e312653dcf317a2bd406f18ffcc507/detection 

Typical Filename: VID001.exe 

Claimed Product: n/a 

Detection Name: Coinminer:MBT.26mw.in14.Talos 

**SHA 256: 47ecaab5cd6b26fe18d9759a9392bce81ba379817c53a3a468fe9060a076f8ca   **

MD5: 200206279107f4a2bb1832e3fcd7d64c  

VirusTotal: https://www.virustotal.com/gui/file/47ecaab5cd6b26fe18d9759a9392bce81ba379817c53a3a468fe9060a076f8ca/details%C2%A0 

Typical Filename: lsgkozfm.bat  

Claimed Product: N/A  

Detection Name: Win.Dropper.Scar::tpd    

**SHA 256: 47ecaab5cd6b26fe18d9759a9392bce81ba379817c53a3a468fe9060a076f8ca   **

MD5: 71fea034b422e4a17ebb06022532fdde   

VirusTotal: https://www.virustotal.com/gui/file/bea312ccbc8a912d4322b45ea64d69bb3add4d818fd1eb7723260b11d76a138a/details 

Typical Filename: VID001.exe   

Claimed Product: N/A   

Detection Name: RF.Talos.80   

**SHA 256: 3a2ea65faefdc64d83dd4c06ef617d6ac683f781c093008c8996277732d9bd66   **

MD5: 8b84d61bf3ffec822e2daf4a3665308c   

VirusTotal: https://www.virustotal.com/gui/file/3a2ea65faefdc64d83dd4c06ef617d6ac683f781c093008c8996277732d9bd66/details%C2%A0 

Typical Filename: RemComSvc.exe   

Claimed Product: N/A   

Detection Name: W32.3A2EA65FAE-95.SBX.TG

The adventures of an extroverted cyber nerd and the people Talos helps to fight the good fight

By understanding the unique challenges of protecting IoT and OT devices, organizations can safeguard these critical assets against evolving cyber threats.

Malleswar Reddy Yerabolu, Senior Security Engineer, North Carolina Department of Health and Human Services

December 5, 2024

4 Min Read

Source: Nicholas Klein via Alamy Stock Photo

COMMENTARY

As Internet of Things (IoT) andoperational technology (OT) devices proliferate across critical infrastructure, manufacturing, healthcare, and other sectors, they bring with them unique and significant security challenges. These devices are increasingly woven into the fabric of everyday business operations, making them essential, yet difficult to secure. While vulnerability management is a well-understood practice in traditional IT environments, IoT and OT introduce complexities that render many of these traditional practices less effective, if not completely obsolete. Here are some of the key challenges, along with strategies for tackling them.

**1\. Device Diversity and Legacy Systems**

IoT and OT environments consist of an eclectic mix of devices that vary greatly in age, functionality, and design. For example, a manufacturing plant might have sensors and controllers that are 20 years old sitting alongside cutting-edge IoT devices. Each device often has a unique operating system and set of protocols, which complicates vulnerability assessments and patch management. Furthermore, many of these legacy systems were designed without security in mind, and their manufacturers may no longer support them.

Solution: Given the heterogeneous nature of these devices, it's crucial to take a risk-based approach. Prioritize the most critical systems and those with the highest vulnerability impact. In some cases, implementing compensating controls, such as network segmentation or increased monitoring, can mitigate risks when patching is not an option.

**2\. Resource Constraints and Limited Patching Options**

Unlike IT systems, many IoT and OT devices have limited processing power, memory, and storage, which makes it challenging to run security software or apply frequent updates. Additionally, many OT devices can't be easily patched or updated without downtime, which can be costly in critical industries like healthcare or manufacturing.

Solution: To mitigate the limitations of patching, consider adopting lightweight vulnerability scanning tools that are specifically designed for IoT and OT environments. Moreover, focus on securing device access by implementing strict authentication controls and isolating critical devices in dedicated network segments.

**3\. Operational Disruption and Downtime**

The need to keep OT systems operational 24/7 is often at odds with the requirements of effective vulnerability management. For instance, in a power plant or factory, even a brief downtime for patching could result in significant financial losses and potential safety risks.

Solution: Careful planning and collaboration between IT and OT teams are essential to manage these trade-offs. Schedule updates and vulnerability scans during maintenance windows and consider redundancy strategies to minimize impact. Additionally, organizations can implement patch-testing in lab environments to ensure compatibility before deploying to production.

**4\. Inadequate Security Protocols and Access Controls**

Many IoT and OT devices lack robust security protocols, making them prime targets for attackers. For example, default passwords and insecure network protocols are common in legacy OT systems, and many IoT devices lack strong encryption or authentication mechanisms. This lack of security leads to increased risk of unauthorized access and exploitation.

Solution: Start by enforcing strict access control policies, such as unique credentials and multifactor authentication. Implementing network segmentation to isolate vulnerable devices from other parts of the network can further limit exposure. Adopting a zero-trust model for IoT and OT environments can also help mitigate the risks associated with inadequate authentication and access controls.

**5\. Limited Security Visibility**

Gaining visibility into IoT and OT environments is challenging, due to their complex and often isolated nature. Many traditional IT security tools are not equipped to monitor these environments effectively, leaving security teams with blind spots that attackers can exploit.

Solution: Organizations should invest in IoT/OT-specific monitoring and security solutions. These tools can provide real-time alerts on suspicious activity and give security teams the visibility they need to identify potential vulnerabilities. Integrating these solutions with security information and event management (SIEM) systems can also help provide a comprehensive view of the entire network.

**Conclusion**

Vulnerability management in IoT and OT environments is not a simple matter of applying traditional IT security practices. These devices require tailored approaches that take into account their unique constraints and critical roles. By adopting a risk-based approach, enforcing strict access controls, and investing in specialized monitoring tools, organizations can begin to address these challenges effectively. While IoT and OT environments may not achieve the same level of security as traditional IT systems, these strategies can help reduce risk and build a more resilient security posture.

Managing vulnerabilities in IoT and OT is a complex but increasingly necessary task. By understanding the unique challenges and implementing targeted solutions, organizations can safeguard these critical assets against evolving cyber threats. After all, security isn't just about what you protect, but how you adapt your strategies to the changing landscape. 

**About the Author**

Senior Security Engineer, North Carolina Department of Health and Human Services

Malleswar Reddy Yerabolu is a senior security engineer with more than seven years of experience in vulnerability management, threat analysis, and security architecture across financial, hospitality, government, and communication sectors. He specializes in leveraging AI, machine learning (ML), and natural language processing (NLP) to enhance threat detection and automate security processes. His research focuses on integrating AI and NLP to optimize cybersecurity solutions. Malleswar’s innovative approach helps organizations reduce risks and strengthen their defenses against evolving cyber threats. He holds a master’s degree in computer engineering from California State University.

Vulnerability Management Challenges in IoT &amp; OT Environments

SUMMARY The machine learning-based threat-hunting system of leading threat intelligence and cybersecurity firm ReversingLabs (RL) recently detected malicious…

****SUMMARY****

*   **Malicious Package Found**: ReversingLabs uncovered _aiocpa_, a Python package targeting crypto wallets via malicious updates.

*   **Unique Attack**: Hackers built trust by publishing a legitimate-looking crypto tool before injecting harmful code.

*   **AI Detection**: ReversingLabs’ _Spectra Assure_ flagged the package using machine learning to detect hidden malicious behaviour.

*   **Action Taken**: PyPI reported, quarantined, and removed the package to stop further harm.

*   **Key Takeaways**: Regular security checks, machine learning tools, and cautious dependency management are vital to combat open-source threats.

The machine learning-based threat-hunting system of leading threat intelligence and cybersecurity firm ReversingLabs (RL) recently detected malicious code in a legitimate-looking package, _“_aiocpa._“_ According to RL’s investigation, shared with Hackread.com, this package was designed to compromise cryptocurrency wallets. 

Through differential analysis of two package versions, RL was able to determine how these attackers carried out their distinctive campaign. The package, a synchronous and asynchronous Crypto Pay API client, has been downloaded 12,100 times.

While probing, researchers identified what makes this campaign unique. Unlike most attacks targeting open-source repositories like npm and PyPI, in this campaign, the threat actors published their own crypto client tool to gradually build trust with a growing user base. Then, they struck. An apparently harmless update to the aiocpa package (version 0.1.13 and later) injected malicious code.

“The malicious actor was observed trying to take over an existing PyPI project named pay, probably to gain access to an established user base, or the attacker estimated that such a package name would attract more victims,” researchers observed.

****How Machine Learning Spotted the Trouble****

RL uses a machine learning-based threat hunting system called Spectra Assure. This system continuously scans open-source packages for suspicious behaviour. In the case of aiocpa, on November 21, 2024, Spectra Assure flagged the updated package due to its resemblance to previously encountered malware.

Further revealed obfuscated code within the aiocpa package with numerous versions published until September 2024. This code was hidden behind layers of encryption and was designed to steal sensitive information like crypto trading tokens. If stolen, this data could be used to drain victims’ cryptocurrency wallets.

Researchers noted in the blog post that application security testing (AST) tools wouldn’t have caught this attack. The malicious code wasn’t present in the referenced GitHub repository, which would typically be reviewed for legitimacy. This is why advanced tools like Spectra Assure are crucial. They analyse code behaviour, allowing for a deeper inspection than traditional methods.

PyPI home page pf the malicious package and the GitHub account behind it (Screenshot credit: RL)

RL reported this malicious package to the Python Package Index (PYPI) for removal, which was later published on their blog on November 25. Researchers at Phylum reported on RL’s discovery, highlighting the uniqueness of the malicious campaign

The incident highlights the evolving nature of open-source software threats making it essential to perform regular security assessments, and consider machine learning-based threat hunting tools for powerful protection. Regular evaluation of third-party code, tools, packages, and extensions is also crucial.

Furthermore, PyPI users should be aware of package name takeover, a serious supply chain infection vector. If a project pay dependency is taken over by a threat actor, a new malicious version could be published to PyPI. The PyPI security team advises users to pin dependencies and versions, using hashes to prevent unwanted updates. 

1.  **ChatGPT Sandbox Flaws Enabling Python Execution**
2.  **PyPI Exploited to Infiltrate Systems Through Python Packages**
3.  **PythonAnywhere** **Cloud Platform Abused to Host Ransomware**
4.  **Qubitstrike Malware Hits Jupyter Notebooks for Cryptojacking**
5.  **VMCONNECT: Malicious PyPI Package Mimicking Python Tools**
6.  **New version of Jupyter infostealer delivered through MSI installer**

“aiocpa” Python Package Exposed as Cryptocurrency Infostealer

This is the first of a series of articles in which we will share how confidential computing (a set of hardware and software technologies designed to protect data in use) can be integrated into the Red Hat OpenShift cluster. Our goal is to enhance data security, so all data processed by workloads running on OpenShift can remain confidential at every stage.In this article, we will focus on the public cloud and examine how confidential computing with OpenShift can effectively address the trust issues associated with cloud environments. Confidential computing removes some of the barriers that high

This is the first of a series of articles in which we will share how confidential computing (a set of hardware and software technologies designed to protect data in use) can be integrated into the Red Hat OpenShift cluster. Our goal is to enhance data security, so all data processed by workloads running on OpenShift can remain confidential at every stage.

In this article, we will focus on the public cloud and examine how confidential computing with OpenShift can effectively address the trust issues associated with cloud environments. Confidential computing removes some of the barriers that highly regulated and defense organizations face when considering public cloud adoption by tackling critical data privacy and security concerns. Specifically, we will discuss some of the common use cases where confidential clusters can be deployed. Red Hat is making a continuous investment in confidential computing, introducing support for a range of use cases in phases. This article describes what’s currently available with the OpenShift cluster and will touch on what to expect in the future.

We are assuming that the reader has some background knowledge of confidential computing and OpenShift. For additional details on those, we recommend reading confidential computing primer and Red Hat OpenShift Overview.

**What is a confidential cluster?**

Enterprises and users are increasingly drawn to cloud services' convenience, flexibility and scalability. Cloud providers offer virtual machines (VMs) to isolate one tenant’s workloads from another tenant’s workloads. While a traditional VM can isolate the workload from other VMs running on the same host, it is still vulnerable to confidentiality-breaches from the hypervisor, virtual machine monitor and the host. Securing sensitive data from external and internal threats when running workloads on infrastructure managed by a third party—the cloud provider—remains a challenge.

One of the solutions to this challenge lies in the use of confidential computing. In the existing security model, we already have ways to implement security controls for data in transit (e.g. https, TLS, etc.) and when the data is at rest (e.g. encrypted disks). Confidential computing is a hardware-based technology that provides confidentiality when the data is in use.

Today, all the prominent architectures either already have or will soon have support for confidential computing in the processor. For instance, on x86, Intel provides Trust Domain Extensions (TDX), and AMD offers SEV-SNP (Secure Encrypted Virtualization—Secure Nested Pages—which supersedes its previous generations of the technologies SEV-ES and SEV). On s390x the feature is available as Secure Execution (SE), Power has a Protected Execution Facility (PEF), ARM is developing the Confidential Compute Architecture (CCA), and finally Confidential VM Extensions (COVE) were suggested for RISC-V platform. While the name, design and implementation vary between the manufacturers and the architectures, at the core, all are meant to solve the same problem.

Confidential computing leverages a Trusted Execution Environment (TEE) to protect the data when in use. A TEE is a confidential trust boundary of memory and CPU, that is trusted and protected. The hardware protects the TEE by isolation (limiting access from outside the TEE) and/or encryption. Therefore, data processed (data-in-use) within the TEE, and the code processing it, are protected.

A confidential virtual machine (CVM) acts as TEE, excluding the host, hypervisor and VM monitor from its trust boundaries. The diagram below illustrates the trust boundary changes for a user application running in a CVM.

Several security technologies are employed to protect the CVM and verify its integrity. Only trusted, digitally signed bootloaders and kernels are permitted to run on the CVM through a process known as Secure Boot. Additionally, the hardware generates a signed attestation report to confirm that the CVM is operating in confidential mode. A virtual Trusted Platform Module (vTPM) can also be utilized to measure and log components running at boot time, such as the bootloader, kernel and their signatures, a process referred to as "measured boot."

A key concept in confidential computing is remote attestation. In simple terms, attestation provides proof that the CVM is indeed confidential and trustworthy before any sensitive data is loaded into its memory. With remote attestation, the CVM sends signed evidence to an attestation server, demonstrating its confidentiality. The server then verifies this evidence to determine whether the CVM can be trusted. This evidence includes the signed attestation report from the hardware, the signed measurements log from the vTPM (if available), and any other relevant items to be attested. Sensitive data (including keys and certificates) can be fetched after a successful attestation.

In an OpenShift cluster with confidential computing enabled, all nodes run on CVMs, so the memory for workloads and their management services is automatically hidden from the host. Further, every new node has to go through remote attestation similar to CVM. Upon successful attestation the node is trusted, secrets are shared and it is allowed to join the cluster (we will dive deeper into attestation for confidential clusters in one of our following articles).

This integration allows users to benefit from the scalability, flexibility and convenience of cloud services through OpenShift while retaining control over their sensitive data. By isolating the OpenShift cluster from the underlying infrastructure, the threat vector is significantly reduced. Consequently, workloads can be executed more securely throughout their entire lifecycle, minimizing the risk of exposure to the cloud provider or unauthorized parties. From the application owner's perspective, the experience is nearly seamless, allowing them to launch a workload with confidential computing just as they would in a standard OpenShift cluster.

This opens up new possibilities for industries storing and processing sensitive information, such as financial services, healthcare and government agencies. They can now migrate their workload from on-prem to the cloud and also execute in the cloud in accordance with regulatory requirements. Some of these use cases are discussed in detail in the following section.

**Main use cases for confidential cluster on public cloud**

Talking to our customers, we are seeing several use cases for confidential clusters. The two main ones being Digital Sovereignty and secure cloud burst.

**Digital Sovereignty**

With the current state of cross-border security and increasing threats to private and governmental organizations, the risk of migrating workloads into the cloud has increased drastically. This has resulted in bringing Digital Sovereignty (for definition please refer to: Digital Sovereignty: Why it pays to focus on independence in digital transformation - PwC) into the spotlight, especially for public IT organizations. Additionally, an emphasis is given to the implementation of zero trust (for definition please refer to: What is Zero trust?). To achieve these objectives, we need a security environment that standardizes and continuously evaluates controls and their implementations. Confidential computing can support both of these use cases.

For Digital Sovereignty, it is important to identify a way to use the cloud compute power with all the advantages of that environment without the cloud concentration risk that comes with it. To do this, procedures need to be implemented which allow migrating from one environment to another while maintaining the necessary high level of security. With the help of confidential computing and especially with the help of confidential clusters, it is possible to move a complete environment from one cloud provider to another without sacrificing any security controls.

Additionally, zero trust is a base for Digital Sovereignty. Confidential computing adheres to this principle with the use of the remote attestation. Whenever a new cluster is moved or, more precisely, a new cluster is created (and the old cluster is destroyed), this new environment is remotely attested, making sure that the environment is running in a confidential mode. Deploying a confidential cluster helps to enable a zero trust architecture.

The ability to move a component, application or cluster from one cloud to the other is also part of several recent regulatory requirements, such as the European Digital Operational Resiliency Act (DORA). DORA requires that data in use is secured. For additional reference, please refer to Chapter II, Section II, Article 8, Paragraph 2 and 3 of DORA and the definition of securing data in use.

DORA also forces companies to document and test their exit strategy from one cloud provider to another in case of a catastrophic failure of the cloud environment. This means companies have to be able to move their whole cloud infrastructure from one environment (cloud provider) to another. OpenShift makes it easier to move components, applications and clusters between cloud providers. OpenShift also provides the same experience for developers and admins regardless of where OpenShift is deployed so they don't have to spend time learning the nuances of each cloud provider’s Kubernetes distribution. Similarly, OpenShift makes it easier to move confidential clusters between cloud providers.

**Secure cloud burst**

There are different use cases when it comes to secure cloud burst scenarios in the public cloud. For example, when the compute requirements are not foreseeable, you need the ability to dynamically grow your available resources. In that case, growing into the public cloud is the easiest option. When you take advantage of the use of consumption based pricing models (like for GPUs) secure cloud burst becomes a cost sensitive model.

Different GPU providers have implemented the extension of a confidential computing model to the GPUs. For instance NVIDIA's implementation—Confidential Computing on NVIDIA H100 GPUs for Secure and Trustworthy AI. Confidential computing becomes an essential technology if you want to securely cloud burst a whole application or even a whole cluster. This usually requires creating a new cluster, deploying the applications and then destroying the original cluster. When doing this with OpenShift, the advantage is that there is almost nothing you need to change in the configuration of the applications or cluster. The secure environment is being provided by the confidential cluster.

**Current availability and future work**

We are rolling out confidential clusters as a solution in multiple phases to enable potential customers and interested users to try it and provide early feedback. These phases are currently planned as follows:

**Phase1**

In Phase 1 users are able to deploy OpenShift clusters leveraging confidential computing technologies on:

*   GCP with OpenShift 4.13 (available as Generally Available with AMD SEV-ES, the support was tested with the instance type n2d-standard-8)
*   Azure with OpenShift 4.14 (available as Technology Preview with AMD SEV-SNP, the support was tested with the instance type Standard\_DC8ads\_v5)
*   No attestation support is available for any of the platforms at the moment

**Phase 2**

In Phase 2 we will extend the solution to include remote attestation capabilities, which will enable the cluster to be deployed as fully confidential and potentially extend its availability on other cloud platforms.

**Phase 3**

In Phase 3 we will introduce confidential clusters as a supported product with full support on both Azure and GCP with AMD SEV-SNP and Intel TDX.

  
More details for the next phases will be shared in future articles.

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