TeamPCP, the threat actor behind an unrelenting flurry of attacks on open-source software this year, has been active much longer than previously thought, according to research Oligo Security shared exclusively with CyberScoop. 

The threat actor, which gained notoriety and has captivated threat hunters as it compromised and injected malicious code into more than 1,000 software packages in less than four months earlier this year, was also responsible for attacks dating back to 2020, Oligo Security found. 

The security vendor’s research team found multiple attacks that bear the markings of TeamPCP, including a late 2025 campaign involving the exploitation of a ShadowRay vulnerability that resulted in the first self-propogating botnet running on hijacked AI infrastructure.

Evidence uncovered during that investigation into the ShadowRay 2.0 campaign was linked to more historical attacks originating from the same IPs, domains and other infrastructure TeamPCP used in attacks that captured widespread attention earlier this year. 

“The scariest thing in this campaign is the speed at which the payloads evolved and changed and adapted to the environment they run in. We saw changes in the speed that we’re not used to seeing in these kinds of attacks. They’re usually slow, careful,” said Uri Katz, director of research at Oligo Security. “This was clearly with the help of AI — the payloads changed rapidly to adjust and change to the environment that they were trying to attack.”

One of the domains that Oligo Security identified in July 2025 was in the profile of TeamPCP’s official GitHub account, said Avi Lumelsky, AI security researcher at Oligo Security. “It’s public, they’re not even trying to hide their identity,” he said. 

From there, Oligo linked TeamPCP to activity tracked under multiple names, including TA-NATALSTATUS and IronErn, spanning from 2020 to late 2025. Much of that activity was traced to the same IPs, domain names, a file server and command-and-control server, researchers said. 

TeamPCP emerged publicly as a brand in late 2025. Soon after, “TeamPCP started to go really broad and do campaigns, which are much more noisy,” said Gal Elbaz, co-founder and CTO at Oligo Security. 

Widespread adoption of AI and TeamPCP’s use of the technology supported this growth as the threat actor built a brand, got more active on social media and boasted publicly about its activities and claimed victims.

“The ability to control the infrastructure and orchestrate the attack with AI was also super new, and I’m sure it helps them,” Elbaz said. 

“All of the companies in the world are in this race to adopt AI because they are afraid their business will die, and they understand, of course, the opportunity. But it’s also what gives the attacker this power to go into it,” he added. “If you don’t really have visibility in what’s going on there or how it behaves, that’s exactly what attackers are after.”

TeamPCP’s more recent attacks have capitalized on new security gaps created by developers’ increasing reliance on AI and the automated systems companies use to deploy code. The threat actor is also consistently wrecking the open-source frameworks and software packages these systems rely on. 

“Most AI infrastructure is open source by design because nobody has the manpower and money to develop everything from scratch,” Lumelsky said. 

“We love open source. We use many of these products ourselves, but it’s all about reading the documentation, and I think many of these tools place the responsibility of using it right and security on the user, and developers are not used to these new kinds of animals,” he added. “That’s why the trust can be exploited at scale.”

As it uncovered a long operational history spanning multiple campaigns, Oligo Security has gained more confidence in understanding how TeamPCP operates. It also means TeamPCP was likely involved in other attacks that haven’t been attributed to it yet or attacks that haven’t been detected. 

“There’s a lot more out there that we haven’t caught or been able to prove up until now,” Elbaz said.

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Amazon’s security researchers say a hacking group tied to North Korea targeted small, little-noticed software packages more than a year before it struck one of the internet’s most widely used programming tools.

The company’s threat intelligence team said Wednesday at a media roundtable at its Arlington, Va., offices that the same group linked to the recent compromise of the open-source axios software library also planted malicious code in a package called typo-crypto in March 2025, a full year before the axios breach. Researchers found the connection while tracing domain records tied to the axios attack back to earlier activity.

“We believe the March 2025 typo-crypto campaign was a rehearsal,” said CJ Moses, Amazon’s chief information security officer, adding that the target’s small scale let the group test its methods “without putting that on the big stage.”

Amazon said the group also compromised two other packages, debug and chalk, in September 2025. Until now, those three incidents had not been publicly linked to the same actor. Security researchers track the group under several names, including UNC1069, Sapphire Sleet and Stardust Chollima. 

Axios, debug and chalk are code libraries used by software developers around the world to build applications. Axios alone is downloaded more than 100 million times a week. “That number represents real organizations putting real code into production systems every single week,” Moses said.

In the typo-crypto case, the malicious file was named “core.js” and was made to look like a legitimate, unrelated package called core-js. Amazon said the file activated only when it received a specific numeric input, then reached out to a server controlled by the attackers to download a second piece of code. That second stage was written differently depending on whether the infected computer ran Windows, macOS or Linux. The code combined encoded text with a cipher, a method Moses said was meant to slow down analysis, including by AI-based review tools, without relying on heavy encryption.

Amazon said the typo-crypto package had few downloads compared with axios, debug or chalk. Researchers believe that initial target served as practice, letting the group refine its approach before turning to more widely used software. “They did what a lot of people do: crawl, walk, run,” Moses said. 

In each of the four cases, Amazon said, the attackers built a relationship with a maintainer who already had access to a package, then used that access to publish an update containing hidden code. “They didn’t break through a window,” Moses said. “They basically earned the trust of an employee to hand them the keys.”

Cybersecurity firm Wiz separately found that about 1 in 10 cloud computing environments were affected by the debug and chalk incident within a two-hour span, a finding Moses cited to illustrate how fast the impact spread. “Going from there not being a vulnerability, to there being a vulnerability, to there being an exploited vulnerability … used to be days to weeks. Now it’s hours to minutes,” he said.

Rick Anthony, senior engineering manager at Amazon Web Services, said the research further shows how attackers face two basic problems in these types of incidents: getting malicious code into a package that will eventually run inside an organization, and keeping that code hidden from developers or security tools. He said groups are increasingly building reputations as legitimate contributors over time. 

“Let me get my package deployed in as many places as possible so that I can spring the trap later,” said Anthony, describing the mindset behind the approach.

Researchers said generative AI has made it easier for attackers to produce code, documentation and contribution histories that look authentic. Anthony also described a technique in which attackers register package names that AI coding tools sometimes generate by mistake, so a developer following an AI suggestion could install malicious software without making any typing error of their own.

The findings come two years after a separate incident involving a program called xz-utils, in which an attacker spent time gaining the trust of the software’s maintainers before inserting a backdoor. Moses pointed to that case as an early example of a pattern now appearing “at scale” and tied to a nation-state.

Since that incident, separate groups have been running roughshod over open-source software. Another group known as TeamPCP has compromised and injected malicious code into more than 1,000 software packages over a four-month span this year. 

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Malware targeting AI coding assistants and software developers’ automated workflows is spreading into more environments with more capabilities, placing defenders at a growing disadvantage.

A malware strain dubbed Sandworm_Mode, first discovered by Socket in February, represents a growing threat to software development. According to a CrowdStrike report, the self-propagating worm can spread through code repositories with minimal detection, raising alarms about software supply chains.

The malware’s capabilities are extensive, but not especially unique compared to the series of supply-chain worms known as Shai-Hulud, and more recently Mini Shai-Hulud.

“This is the new trend,” Adam Meyers, senior vice president of counter adversary operations at CrowdStrike, told CyberScoop. “This is something we’re seeing more and more. It’s the new hotness right now.”

Sandworm_Mode targets and steals sensitive data, including credentials, keys and secrets that unlock paths to additional services and dependencies throughout the AI toolchain. This includes AI assistants, cloud providers, API keys for nine major LLM providers, CI/CD pipelines and automated systems that build, test and publish code.

These actions blend in with tens of thousands of other commands occurring daily in any given environment infused with AI development tools. 

“Trying to find the signal of something malicious happening is very difficult because there’s so much noise out there,” Meyers said. 

The worm also paces itself, setting multi-day delays to separate initial access from follow-on malicious activity — creating a gap in victims’ telemetry windows, which makes it even more challenging for defenders to detect and attribute the chain of infection properly. 

“AI agents are pulling down all of these different dependencies continuously throughout the day,” Meyers said. “When you’re looking downrange from the perspective of the security operations team, you’re just seeing everybody pulling down these dependencies, and these dependencies self-unpacking and executing, so it just gets really, really noisy to try to find something bad happening.”

The malware covers its tracks further with a bit of a mean streak, by automatically destroying compromised environments if it can’t spread or accomplish its objectives.

“It’s well thought-through, and well developed, so somebody spent some time caring and feeding this thing,” Meyer said.

Despite CrowdStrike’s four-month review of Sandworm_Mode, the cybersecurity firm has yet to gain a firm handle on its intent, but Meyers said it is designed to attain a strong foothold, which could enable long-term access.

CrowdStrike hasn’t determined who is responsible for the malware, yet Meyers said he doesn’t think TeamPCP, a threat group that’s been on a rampage through open-source software this year, is involved. 

“It could be a nation-state threat actor, or it could be an e-crime actor that’s looking to use this to then sell access to other organizations,” he said. “We don’t really know what the intention is.”

The state of Sandworm_Mode and whether it remains active is also unclear. CrowdStrike said it continues to observe recently active malicious supply-chain packages that follow similar but technically divergent patterns.

Ultimately, “the world has changed,” Meyers said, adding that many attackers are pursuing similar paths in the AI toolchain, requiring defenders and threat hunters to place a greater focus on this burgeoning mode of aggression.

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