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Providers and deployers of AI systems: You only have a couple of weeks left until you must explicitly inform users when they are interacting with AI content.

To assist in the effort, the European Commission (Commission) has published guidelines to help AI deployers get in line with the AI Act’s transparency obligations, which will begin to go into effect on August 2.

After that, companies providing AI systems must alert users when they are interacting with AI. They must also tell users when they have been exposed to deepfakes, “emotion recognition,” or biometric categorization systems, or when they are given AI-manipulated content in matters of “public interests without human review or editorial control.”

Henna Virkkunen, the Commission’s executive VP for tech sovereignty, security and democracy, said in a statement, “with today’s guidelines, the Commission supports the smooth and effective application of the AI Act to make AI systems interacting with people such as chatbots and AI agents and AI content more transparent and trustworthy. These guidelines support providers and deployers in meeting their obligations under the AI Act, while helping citizens know when they are interacting with AI.”

Systems must include machine-readable markers to reveal such content, to reduce “the risk of deception and manipulation” and build public trust in AI.

“Generative systems have collapsed the cost of producing convincing content while the cost of judging it stands where it always stood,” said Sanchit Vir Gogia, chief analyst at Greyhound Research. This requirement is “an attempt to restore friction to that imbalance.”

A company’s non-compliance could result in fines anywhere from €750K (about $856K) to €15M (about $17 million), or even up to 3% of its total worldwide annual revenue.

Transparency requirements

The EU AI Act’s transparency requirements apply to “natural or legal persons,” public authorities, agencies, or other bodies that develop AI systems, or have them developed, and place them on the EU market or into use under their name or trademark. This means all companies, regardless of whether or not they are EU-based.

“Systems placed on the European market, put into service there, or producing outputs used there are inside the field, wherever the developer sits,” Gogia noted.

Applicable systems must be intended to interact directly with “natural persons”; these systems include AI-enabled chatbots or conversational agents, AI companions, or coding agents. However, AI-enabled tools like recommender systems, spam filters, authentication, search and retrieval, transcription, text and code auto-completion, or predictive maintenance do not fall under the rule.

Specific outputs such as AI-generated text, images, video, and audio must contain a machine-readable mark. Deepfakes and public interest-related text created by AI without human review or control must be clearly labeled, however, deepfake content that is “artistic, creative, satirical, or fictional” is largely exempt.

AI content must be marked with one of three labels: “AI,” “Fully AI-generated,” or “Partially AI-modified.” For instance, “Fully AI-generated” applies when news summaries, music, art, or videos have been created without any human oversight (apart from prompting), while “partially AI-modified” could mean a person’s face is swapped into an authentic photograph to create a deepfake.

The three icons are publicly available for free use; enterprises can download zip files in PNG and SVG formats.

Most of the Act’s transparency rules begin to go into effect on August 2. But AI systems placed on the market before then will have some leeway; they must be in compliance by December 2.

However, a four-month allowance “on one obligation, for one population of systems, contingent on one procedural step, is not a strategy,” Gogia emphasized. Enterprises should plan to comply by August 2 and “treat any relief that arrives as margin.”

A consistent code of practice

Along with the transparency guidelines, the Commission has introduced a code of practice that essentially serves as a gesture of good faith. When signed, it can provide “legal certainty” and a “simple and practical” way to demonstrate compliance with the AI Act, according to the Commission. Signatories can also collaborate through the ‘Signatory Taskforce,’ which will share practices and advance technologies around marking and labeling practices.

Providers that choose not to sign must comply through other methods and demonstrate that those methods are “adequate” through assessment by surveillance authorities, according to the Commission.

Non-signatories “keep their flexibility, and will face more case-by-case scrutiny for it,” said Gogia.

Criteria for compliance

Shashi Bellamkonda, principal research director at Info-Tech Research Group, pointed out that the transparency requirements apply to content only when three criteria are met: It has been published, is informative to the public, or is on matters of public interest.

B2B business content or blogs may not need an AI disclosure if they do not meet these criteria, he noted. Also, published text that has undergone human review or is under editorial control does not need to be labeled. Editorial control means that a person must hold the ultimate legal responsibility for the publication of the content.

Many companies like Google, Adobe, and LinkedIn have already established ways to identify images marked as AI-generated. Meta has made it a requirement, but the creator has to add the AI-generated label, Bellamkonda said.

“This is a good move for guardrails around public information, and companies with good compliance and ethical oversight may not have to worry about this,” he noted. But as a general practice, companies should disclose AI-generated content and state whether it has been human reviewed.

Creating a transparency pipeline

Establishing full transparency means identifying who carries the responsibility for the content, whether the marking survives real use, not just testing, and what evidence will defend the decision, Gogia said.

Concerns cluster around responsibility, durability and evidence. Several organizations usually touch one piece of content, and none controls the whole chain, which is why contracts become the “pressure point,” he said. Most current agreements were written to deliver software and say “almost nothing” about provenance persistence, verification access, or evidence retention.

The durability concern is the most difficult, Gogia noted, because marking performs well in controlled settings but “badly in ordinary life.” Meta, for one, said its invisible watermark was designed to survive cropping; a published test, however, found the company’s preview detector missed 55% of cropped images.

“CIOs should ask which platform can actually provide evidence before believing its dashboard,” said Gogia.

Disclosure of AI use must be “clear, distinguishable and accessible,” he emphasized. “A notice buried in lengthy terms, or reachable only through determined clicking, satisfies nobody, least of all a market surveillance authority.”

Sustained compliance is a “living control” requiring a central record of systems, duties and evidence; testing taking place where the user meets the control rather than where the developer built it; and continuous supplier assurance. Enforcement will vary by country, so keep one common baseline with local overlays, Gogia said.

His advice: Inventory every system that talks to people, generates content, or gauges sentiment; classify provider and deployer roles; place disclosures at first interaction; define substantive human review; keep the evidence.

Marks and provenance signals should be tested after content undergoes cropping, compression, translation, transcription, and other editing, Gogia said. A useful audit starts from a real output and follows its “pulse” through generation, editing and publication, identifying at “each beat” the responsible party, the surviving mark, and evidence for exceptions. Missed labels should also be traced for root cause and recurrence.

To ensure compliance, before August 2, enterprises need a prioritized inventory, live disclosures on the highest-risk use cases, and a “named owner for every control,” he noted. In the first 30 days, they should stabilize and test; in the first 90 days, push requirements into procurement processes as a standing discipline. Procurement must secure commitments on marking methods, known failure modes, and evidence access, with explicit notice if/when any of them change.

“The sensible architecture is a common transparency baseline carrying traceability, responsibility, and evidence, with jurisdictional overlays for language, sector rules, and local practice,” Gogia said.

This article originally appeared on CIO.com.

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Cambridge University researchers say launch costs fell from $87,000 to $3,868 per kilogram between 1960 and 2025—or roughly 96%—and could hit $273 by 2040.

Rapidly falling launch costs are making space more accessible than ever. But new research suggests the economics are improving even faster than most people realize, potentially opening the door to entirely new industries beyond Earth.

For most of the space age, the cost of getting material into space was so vast that only the most well-heeled governments and corporations could participate. In 1960, getting a kilogram of payload into orbit would have cost you more than $87,000 (in 2024 US dollars).

But according to researchers at the University of Cambridge, that figure had collapsed 96 percent to $3,868 by 2025. The team’s modeling suggests this trend will continue apace for at least the next few decades, with prices forecast to hit just $1,569 by 2030 and as little as $273 by 2040.

The rapid decline in prices is thanks to a well-established economic principle known as Wright’s Law, which holds that technologies get predictably cheaper as cumulative production grows. The Cambridge team says the trends seen in launch costs could soon make a host of possibilities previously confined to science fiction commercially viable, including orbital solar power, asteroid mining, and space-based manufacturing.

“Space is no longer a science-fiction fantasy or a purely scientific pursuit, it is becoming a marketplace,” Alessio Terzi, who led the study, said in a press release. “Rapidly falling launch costs could open the way to space colonization and commercial activity far beyond low Earth orbit.”

To conduct their study, published in PNAS Nexus,the researchers assembled a massive dataset of rocket launches covering over 4,400 flights by more than 330 different rocket designs from 1960 to 2025. For each launch, they estimated the “unit flyaway cost,” or the total cost to manufacture, maintain, and launch the vehicles, excluding research and development investments.

They then checked how this data stacked up against Wright’s Law, which predicts that every time production volumes double the cost should fall by a fixed percentage. This is known as a technology’s “learning curve” as the reduction in costs is attributed to an industry getting better at producing the technology with experience.

The researchers found space launches obey the law almost perfectly, with every doubling of payload sent to orbit shaving 21.2 percent off the average cost per kilogram. More importantly, this represents a particularly steep learning curve compared to previous technologies.

Solar panels are often held up as the poster boy for learning curves, with prices falling 99.8 percent between 1975 and 2023. But while solar power’s total price reduction is higher than that achieved by launch vehicles, the technology got there by scaling deployment far more. When accounting for total production, solar’s learning curve lags launch costs at 20.2 percent.

The researchers also compared launch costs to another revolution in transport. Steamships transformed our ability to ship goods like wheat and cotton around the world in the 19th century. They found that steamship costs only fell 15.5 percent with each doubling of cargo.

“The cost of space launch technology is now falling faster than during one of history’s greatest transport revolutions,” said Terzi. “Steamships cut costs through explosive growth in global trade. Space technology, by contrast, has achieved even steeper declines at a far smaller scale. This suggests there is plenty of scope for further cost reductions and the industry may now be on the cusp of a comparable economic boom.”

There are, of course, caveats. The researchers note that the industry’s progress is inextricably tied to the fate of a single company. SpaceX already accounts for roughly 80 percent of payload reaching orbit. If the company successfully scales up its reusable, heavy-lift Starship vehicle it could massively reduce costs.

But a company with a stranglehold on the global launch market may be tempted to take advantage of its monopolistic position. This may also push foreign governments and companies away from relying on SpaceX even if it’s the cheapest option.

There’s also the danger that as costs fall and launching material into space becomes more accessible, low Earth orbit could quickly become clogged with debris that makes it increasingly difficult to reach orbit safely.

If these challenges can be sidestepped, the implications of such rapidly falling costs could be profound. The researchers suggest that everything from zero-gravity research and orbital tourism to factories churning out fiber-optic cables and 3D-bioprinted organs could become financially viable.

The post Spaceflight Nears Its Steamship Era appeared first on SingularityHub.

Stačí svátek a víkend a z jednoho termínu jsou rázem tři různá data. ČSSZ trvala na tom, že přehled OSVČ musí být podán do 1. června 2026, daňový poradce však podle zákona vypočítal lhůtu až na 4. června. Jeho výklad nakonec potvrdilo i Ministerstvo práce a sociálních věcí.

Abyste dosáhli na odškodnění za neplatný vyhazov, nestačí jen prokázat jeho protiprávnost. Musíte být i připraveni znovu nastoupit do práce. Co když si mezi tím požádáte o předčasný důchod?

Už jsme se věnovali popisu knihovny gg určené pro vykreslování 2D grafiky. Dnes popis dokončíme a navíc se zmíníme o knihovnách gg-pdf a gg-svg sloužící k exportu 2D grafiky do vektorových formátů PDF a SVG.

Tisková zpráva společnosti NewEgg objasnila, proč je to s cenami Ryzen 7 7800X3D tak, jak to je. Microcenter zlevnil Ryzen 7 7800X3D prostě proto, že Ryzen 7 7700X3D vůbec nebude prodávat…

Hledáme člověka, který umí počítat. Hlavně se zdroji. Tiskové zprávy přepisovat nebudeš. Kalkulačku dodáme, zvědavost ne. Podezřívavost vítána. Musíš umět psát a občas někomu zkazit tiskovou zprávu. Umíš hledat chyby dřív než naši čtenáři? Pojď k nám.

If you use WordPress, patch now. Just hours after fixes came out, attackers have begun exploiting two bugs that, when chained together, allow pre-authentication remote code execution (RCE). And security researchers tell us there’s a very good chance the miscreants had an AI assist. “Once the vulnerabilities were publicly disclosed, reproducing them with the help of frontier AI models was only a matter of time and tokens,” Jake Knott, watchTowr principal security researcher, told The Register. “WatchTowr was able to trivially reproduce CVE-2026-63030 within minutes of disclosure, and the second CVE-2026-60137 with some additional effort.” WordPress released patches for both CVEs late Friday, but by Saturday it was game over. “By the early hours of Saturday morning, successful exploitation was already well underway, initially using public exploit code to exfiltrate hashed credentials, with remote code execution following once additional details were made public,” Knott said. “From our vantage point across a global client base, we are seeing widespread impact of this vulnerability across organizations of every size and every vertical.” Here are the details about both security holes, and what went down since WordPress revealed and fixed them on Friday. CVE-2026-60137 is a moderate-severity SQL injection issue, and CVE-2026-63030 is a critical REST API batch-route confusion bug. “A route confusion flaw causes the arrays containing the sub-requests, validation results, and matched handlers to become misaligned,” Hacktron researchers explained. This causes WordPress to become confused about which requests have been properly validated and thus treat all requests as trusted, including those that it should block. Individually, the bugs are difficult to exploit. But when chained together, they can wreak havoc on any organization using a vulnerable WordPress version because they allow unauthenticated RCE. WordPress 6.9 is affected by both vulnerabilities, and version 6.9.5 contains fixes for both, while WordPress 6.8 is only affected by the SQL injection flaw, and version 6.8.6 fixes it. Additionally, WordPress 7.1 Beta 1 is also vulnerable. Version 7.1 Beta 2 fixes both CVEs. Versions of WordPress prior to 6.8 are not affected. John Blackbourn, one of the WordPress core developers, recommended affected users “update your sites immediately.” Because of the flaws’ severity, the WordPress security team “enabled forced updates via the auto-update system for sites running affected versions,” he added. The content management system credited Searchlight Cyber researcher Adam Kues with finding and reporting CVE-2026-63030, and in a subsequent Friday advisory, Kues dubbed the bug wp2shell. “The attack has no preconditions and can be exploited by an anonymous user in a stock install of WordPress with no plugins,” Kues said, adding that his security shop released a free wp2shell checker to determine if your instance is vulnerable. Security firm PatchStack reported exploitation of both CVEs as of Friday night, but didn’t provide details about the attacks. VulnCheck’s research team, which also began researching the patches on Friday, verified more than two dozen unique proof-of-concept exploits targeting WP2Shell as of Sunday. “After public exploit code was released, attackers began spraying the internet indiscriminately, hitting anything reachable and trying to get lucky,” Knott told us. “Our honeypots recorded tens of thousands of exploitation attempts, and more than 100 backdoor accounts created by different threat actors using variations of public tooling.” After creating these backdoor admin accounts, watchTowr observed attackers deploying fake WordPress plugins to achieve RCE, exfiltrate credentials or secrets, or download additional tooling to further compromise the system, he added. “In one case, we watched a threat actor repeatedly attempt to pull down Overlord RAT, a Golang-based remote access trojan.” Any orgs that waited until Monday to patch are likely already compromised, Knott warned. “Defenders need to inspect their WordPress instances for new administrator accounts, malicious plugins, or other suspicious files, regardless of whether they’ve patched,” he said.®

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Real FBI agents won't slide into your DMs and offer to help you recover stolen funds. The bureau's Internet Crime Complaint Center (IC3) updated an earlier warning on Monday about scammers impersonating the agency online, saying fraudsters continue to use the scheme "to deceive and revictimize individuals." According to IC3, there are two different schemes being used to target cybercrime victims, both directly and by soliciting them to report incidents. In the first scheme, IC3 said scammers create fraudulent social media profiles and pages impersonating FBI personnel or IC3. They may also infiltrate online groups for fraud victims or contact victims directly while claiming to represent the FBI or the complaint center. In other cases, victims are being contacted by someone claiming to be an FBI agent after realizing they were approached by someone trying to scam them and saying they intended to report the incident to the FBI or file an IC3 complaint. The FBI said the impersonator then directs victims to a fake IC3 update page or continues communicating through messaging apps. In the other instance, scammers are creating AI-generated videos on social media depicting senior FBI officials and directing users to a spoofed IC3 website to report cybercrimes they may have fallen victim to, with the scammers then collecting the information and using it to contact victims for further fraud. AI-generated depictions of public figures are similarly being used to make such scams appear legitimate. “Some individuals received an email or a phone call, while others were approached, or observed an advertisement via social media or forums,” the IC3 said. “Almost all complainants indicated the scammers claimed to have recovered the victim's lost funds or offered to assist in recovering funds.” Regardless of how legitimate social media profiles look, or how realistic those AI-generated videos may be, the IC3 is warning that none of them should be believed for a simple reason: The IC3 doesn’t have a social media presence of any kind, and it doesn’t investigate crimes or offer to recover lost funds through social media. “Any social media profiles or pages claiming to represent IC3 or offering to recover lost money are fraudulent and are actively attempting to steal your personal or financial information,” the IC3 warned. “IC3 will never directly communicate with individuals via phone, email, social media, phone apps, online chat, or public forums.” The IC3 said that any contact made with a cybercrime victim who reports an incident via its actual website will be made by an FBI employee from a local field office or other law enforcement official. Here’s another hot tip: If you fall victim to a cybercrime or online scam, don’t post about it on social media - that’s only going to invite someone with bad intentions to seek you out. ®

AI datacenters wreak havoc on the power grid under normal circumstances, so what happens if a bad actor controls all the GPUs and wants to cause harm? Cybersecurity researchers in China have devised a way for malicious tenants to attack their infrastructure provider, potentially causing blackouts or damaging equipment. The attack, dubbed Bit2Watt, imagines an adversary masquerading as a legitimate cloud tenant to launch GPU workloads that have the potential to damage datacenters and supporting electrical systems. It's intended to demonstrate the need to extend cybersecurity defenses to datacenter workload scheduling. The researchers, Zhouhao Ji, Kaikai Pan, and Wenyuan Xu, from Zhejiang University in Hangzhou, China, describe their technique in a preprint paper titled "Bit2Watt: A Cyber-Physical Vulnerability Exploiting GPU Workloads Across Power and Computing Infrastructures." AI training workloads represent a known challenge for datacenter operators. As Microsoft, Nvidia, and OpenAI noted in a 2025 research paper arguing the need for power stabilization during AI training, the transition from GPU computation to GPU data synchronization causes large power swings to occur. And if the frequency spectrum of these power swings is "harmonized with critical frequencies of utilities, [that] can cause physical damage to the power grid infrastructure." Meta's paper on the training of Llama 3 also cites the risk AI training poses to the power grid. It says, "During training, tens of thousands of GPUs may increase or decrease power consumption at the same time, for example, due to all GPUs waiting for checkpointing or collective communications to finish, or the startup or shutdown of the entire training job. When this happens, it can result in instant fluctuations of power consumption across the datacenter on the order of tens of megawatts, stretching the limits of the power grid." Bit2Watt weaponizes this scenario by proposing that an adversary could use malicious GPU workloads to destabilize the datacenters and electrical infrastructure. "Our results indicate that GPU loads can reach modulation frequencies exceeding 6,000 Hz, compared with only a few hertz observed in conventional household loads such as air conditioners," the Zhejiang University authors state in their paper. "Such high-frequency modulations can substantially induce voltage excursions, harmonic distortion, and damping degradation." The authors claim an attack on a 1-MW local power grid consisting mainly of distributed energy resources like photovoltaics could use 1,000 GPUs to create a total harmonic distortion of 46.8 percent, which would squander nearly half the electrical current on non-productive work and would throw off about 20 percent more heat than normal. "This not only threatens the availability of the computing equipment but also produces a negative damping ratio of -0.27, introducing an unstable mode into the system," the authors contend. "Once the protections are triggered and computing loads are shed, it can trigger cascading failures, potentially leading to blackouts exceeding 80 percent in large-scale power systems." The attack is relatively covert, the authors argue, because it can be launched within authorized workload execution paths and would likely be missed by cloud-provider monitoring frameworks. Thus, they propose that infrastructure providers coordinate defenses across the cyber and physical layers to look for malicious computation patterns. They also emphasize the need for local energy buffering systems to handle power demand spikes. Bit2Watt also potentially opens the door for a side-channel attack called Watt2Bit. The researchers note that the electrical and thermal stress on hardware from a malicious workload creates denial of service events and enables the covert exfiltration of data via power modulation. As a proof of concept, they showed they could recover a 50-bit test sequence using frequency-shift keying (FSK) encoding. "These findings underscore a fundamental shift: as power and computing infrastructures converge, security must be addressed across domains, requiring coordinated defenses that consider workload behavior, power electronics, and grid dynamics," the authors conclude. ®

Apparently, being a leading destination for AI development doesn't mean AI will bail you out. AI agents broke into Hugging Face's production infrastructure, but commercial LLM guardrails blocked the forensic investigation, forcing it to turn to a Chinese open-weight model instead. The intrusion, “driven, end to end, by an autonomous AI agent system,” compromised a “limited set” of Hugging Face’s internal datasets and “several” credentials used by its services, according to a Thursday security incident disclosure. While the ML platform says that it’s still investigating whether any partner or customer data was exposed in the breach, there’s “no evidence of tampering with public, user-facing models, datasets, or Spaces, and our software supply chain (container images and published packages) was verified clean.” It also doesn't know which model the attackers used to power a swarm of AI agents, which, we're told, executed many thousands of individual actions across short-lived sandboxes, using self-migrating command-and-control staged on public services. “This matches the ‘agentic attacker’ scenario the industry has been forecasting,” according to the Hugging Face blog. Additionally, after unsuccessfully using unnamed frontier models to start the forensic analysis, the Hugging Face security team ultimately ran the log analysis on GLM 5.2, an open-weight model developed by Chinese AI firm Z.ai, on the platform’s own infrastructure. The advanced commercial models didn’t work because their analysis required submitting real attack commands, exploit payloads, and command-and-control artifacts - all of the things that the LLMs’ guardrails have been trained to block so that the AI systems can’t be used in real-life attacks. “The attacker was bound by no usage policy, while our own forensic work was blocked by the guardrails of the hosted models we first tried,” the security team wrote, noting that it’s not arguing against safety measures on hosted models and has shared this information with the LLM providers. Using GLM 5.2 had another benefit, Hugging Face noted: “No attacker data, and none of the credentials it referenced, left our environment.” This also serves as an important reminder to defenders, according to the AI platform. “Have a capable model you can run on your own infrastructure vetted and ready before an incident, both to avoid guardrail lockout and to keep attacker data and credentials from leaving your environment.” The Hugging Face intrusion is yet another indication that attacks carried out by autonomous AI agents are no longer a future threat, but rather the current state of AI-based intrusions. Last week, The Register spoke with TrendAI VP of AI and security threat research Tom Kellermann about another recent attack, during which a jailbroken Google Gemini did 90 percent of the work - including spinning up a new C2 server in just six minutes. The human did just 10 percent. Additionally, earlier in July, Sysdig threat hunters documented what they say is the first-ever documented agentic ransomware infection with an LLM - not a human - driving the entire extortion operation, from gaining initial access to compromising a production database server and destroying data. “Think of a burglar that never gets tired, never needs sleep, and instead of jiggling one door handle at a time, is trying a thousand of them simultaneously,” Zero Networks field CTO Chris Boehm said in an email to The Register about the Hugging Face intrusion. “That's basically what happened here. Not one guy typing commands into a terminal, a swarm of little automated processes hammering away nonstop, hopping between hiding spots to make it harder to trace,” Boehm said. He added, the “part that actually unsettles” him most is that the platform’s security team couldn’t get commercial AI tools to help analyze the attack, “because those tools were built to refuse anything that looked like a real attack command. It didn't matter that it was the good guys asking.” Boehm said the takeaway for security teams is twofold: “These agents can now move faster and more relentlessly than any human ever could, and the safety tools we're building aren't always ready to help us respond at that speed.”®

Zákaz používání mobilních telefonů a dalších elektronických komunikačních zařízení ve školách, jehož uzákonění navrhli jako poslanci premiér Andrej Babiš (ANO) a ministr školství Robert Plaga (za ANO), dnes podle očekávání vláda podpořila. Novinářům to oznámil Babiš, podle Plagy byla podpora kabinetu jednomyslná. Účinnost předkladatelé navrhují od 1. září 2027. Podle opoziční ODS je plošný zákaz líbivé populistické opatření namířené proti digitální gramotnosti dětí.

Cybersecurity researchers have discovered nearly 7,600 malicious GitHub repositories, out of which more than 800 pose as artificial intelligence (AI) skills or Model Context Protocol (MCP) servers to deliver a malware family known as SmartLoader as part of an ongoing campaign codenamed FakeGit. "FakeGit uses copied projects, lookalike developer profiles, convincing READMEs, and malicious ZIP

Cybersecurity researchers have discovered nearly 7,600 malicious GitHub repositories, out of which more than 800 pose as artificial intelligence (AI) skills or Model Context Protocol (MCP) servers to deliver a malware family known as SmartLoader as part of an ongoing campaign codenamed FakeGit. "FakeGit uses copied projects, lookalike developer profiles, convincing READMEs, and malicious ZIP Swati Khandelwalhttp://www.blogger.com/profile/[email protected]

A malicious component dubbed HollowGraph uses the calendar feature in compromised Microsoft 365 mailboxes as a command-and-control channel to receive attacker commands and exfiltrate stolen data. [...]