Microsoft again asked Entra ID administrators to migrate users to phishing-resistant methods to avoid sign-in disruptions before it retires SMS and voice authentication in February 2027. This retirement process applies only to Microsoft Entra ID workforce tenant authentication scenarios and not to Azure AD B2C or Microsoft Entra External ID customer identity scenarios. Before Microsoft retires SMS and voice authentication, admins should ensure all users in their organizations use a phishing-resistant method, since they will no longer be able to use them to complete multifactor authentication and log in to their accounts. Admins can choose from passkeys, QR code authentication, FIDO2 security keys, and other Entra ID-supported sign-in methods. "Microsoft-provided SMS and voice authentication will retire starting February 1, 2027. Complete your migration before rollout begins to avoid interrupting users' sign-in experience," Microsoft said in a Microsoft 365 Message Center update on Tuesday.
Discover-Tech allegedly targeted Starlink users with digital ads to track their locations, according to sources cited in a new Reuters report. Digital defense firm TrendAI found that an Israeli ad tech company was heavily targeting users of satellite internet service Starlink, probably to spy on them. That’s according to six people familiar with the matter, speaking to Reuters. Raphael Satter reported it on October 27 in a Reuters story, and the claims rest on sources, not on a published attribution. “Researchers at TrendAI, a unit of Tokyo-based cybersecurity company Trend Micro, concluded the Israeli company Discover-Tech was one of the biggest sources of digital ads shown to users of SpaceX’s Starlink service and that the ads were likely being used to geolocate or otherwise surveil them, according to the six people.” Reuters states. TrendAI concluded that the company Discover-Tech was one of the biggest sources of digital ads shown to users of SpaceX’s Starlink. They believe the ads were likely used to geolocate users or otherwise surveil them. “TrendAI Research observed large-scale use of advertising infrastructure for geolocation tracking, advertising technology surveillance, and intelligence gathering. Data from these activities is valuable for precise targeting of key individuals in sensitive locations, including active conflict zones.” reads the report published TrendAI. “SHADOW-EARTH-79 is also the number one bidder in 105 individual countries in Starlink traffic that we observed. It accounts for approximately 13% of all winning bid events in Starlink traffic, five times higher than average (approximately 3%) bids for other bidders, and the highest of any high-volume buyer. Starlink is widely used in conflict zones where terrestrial networks are degraded.” SpaceX didn’t respond to requests for comment, and Discover-Tech and its chief executive didn’t respond over the past two weeks. Starlink users make attractive targets. Governments around the world are trying to get a grip on satellite internet terminals, which route data through SpaceX satellites and not through nationally regulated telecom firms. That lets them sidestep local internet restrictions, work in hostile areas or coordinate action across battlefields. Ukraine’s military relies on Starlink for frontline communications and for directing drone strikes. The findings come from advertising data collected by TrendAI. The data shows that Discover-Tech became one of the biggest bidders for ads shown to Starlink users worldwide. It was the top bidder in more than 100 countries, including several where Starlink is banned or restricted. Advertisers bid in online auctions to buy space for ads in browsers and apps. “In Starlink IP space traffic that we observed, SHADOW-EARTH-79 is the second-largest winning bidder by raw volume. However, examining the statistics and saturation of the group’s ad impression buying strategy reveals an obvious skew towards buying ad impressions on Starlink addresses, compared with its overall footprint.” continues the report. TrendAI published its report on October 15 but didn’t name Discover-Tech. Instead, it identified “an ad tech entity” called Shadow-Earth-79. Six sources say that’s TrendAI’s codename for Discover-Tech. TrendAI didn’t directly explain why it left out the company’s name. It said its naming policy helps prevent mistakes and avoids labels that could confuse security teams, lead them to focus on the wrong risks or prompt the wrong response. Starlink users are valuable targets for surveillance. Governments want more control over satellite internet services, which send data through SpaceX satellites rather than local telecom networks. Starlink lets users get around local internet restrictions, stay connected in dangerous areas and communicate on the battlefield. Ukraine’s military uses Starlink for frontline communications and to help direct drone strikes. Finding ways to track Starlink users has turned into a cottage industry. In May, the Israeli newspaper Haaretz and the website Intelligence Online separately reported that Israeli-owned businesses were pitching clients on ways to identify and track them. Haaretz said exploiting ad data appeared to play a key role. On the same day as TrendAI’s report, the Canadian cyber watchdog Citizen Lab and the New York ad tech firm Confiant named Discover-Tech. Both said it abused the ad bidding process, which can leak data about internet users back to the bidder. Over time, a bidder can collect that data, collate it and merge it with other information to de-anonymize users and follow them around the web. In some cases it can also set them up for targeting with surveillance software. Citizen Lab and Confiant said the ads appeared inside dozens of sensitive networks belonging to media organizations, governments and tech firms. Google, Comcast and other companies said they removed Discover-Tech from their ad platforms. At least one big US tech company and one international organization recently started internal inquiries into whether Discover-Tech’s ads targeted their employees, according to one of the six people and a seventh person familiar with the matter. TrendAI’s report pointed to suspicious bidding patterns that suggested “targeting and tracking infrastructure” and not a commercial advertising operation. “Overall, the design of this “customer-facing” front-end makes us believe that the system is more likely designed as a “surveillance” and “intelligence gathering” platform, rather than simply a platform for advertisement management.” the report concludes. “The collected evidence indicates with moderate-to-high confidence that SHADOW-EARTH-79’s advertising presence functions as targeting and tracking infrastructure rather than a commercial advertising operation. The anomalous bidding behavior, heavy dominance in sanctioned and conflict states, and pronounced over-bidding for Starlink address space establish intent to reach specific audiences in sensitive geographies.” It noted an obvious skew toward Starlink-aimed ads. It also found that Shadow-Earth-79 was the top ad buyer in Syria, Libya, Yemen and South Sudan, and the second biggest in Afghanistan. Few Western brands are chasing shoppers in Libya at the moment, and the report says demand for legitimate Western advertising in sanctioned or active-conflict states is effectively zero. The entity also won an implausibly dominant share of bids in several other countries, including Hungary, Israel, Egypt, Azerbaijan and Venezuela. The researchers were convinced Discover-Tech was behind it and discussed naming it in the report, according to the six sources. They dropped the idea after TrendAI executives raised legal concerns, five of those sources said. It wouldn’t be the first time. Earlier this year, Reuters reported that Palo Alto stripped explicit references to China from a report on a global cyberespionage campaign, even though its researchers were confident Beijing was behind the hacking. Reuters said the report was watered down over fears that naming China would cause problems for Palo Alto’s operations there, which were already under scrutiny after a Beijing directive told domestic companies not to use its products. Palo Alto said the lack of attribution had nothing to do with China’s procurement rules and called any suggestion otherwise speculative and false. Executives fear that exposing surveillance operations could draw retribution, and industry experts tell Reuters the sector has a habit of staying quiet. “Self-censorship is common in the cybersecurity industry, especially when executives fear that exposing surveillance operations could draw retribution, industry experts say.” Reuters concludes. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, Starlink)
Attackers have begun probing the Internet for systems unpatched against a recently disclosed critical Oracle E-Business Suite (EBS) vulnerability. Discovered in a core component of EBS's Application Object Library and tracked as CVE-2026-101767, this flaw lets unauthenticated threat actors with HTTP network access take over vulnerable systems in low-complexity attacks. Oracle released security updates to address the issue in its October 2026 Critical Security Patch Update on October 20 and urged customers to patch their systems immediately. "In some instances, it has been reported that attackers have been successful because targeted customers had failed to apply available Oracle patches," it said. "Oracle therefore strongly recommends that customers remain on actively-supported versions and apply security patches without delay."
CVE-2026-97631: A 16-year-old UEFI flaw (CVSS score of 9.5/10) enables pre-OS code execution. Exposed servers need firmware patches and checks. A critical flaw, tracked as CVE-2026-97631 (CVSS score of 9.5), in the firmware that boots most of the world’s servers is now public, and the patch details came out months early. The bug affects TianoCore EDK II, an open-source project used by hardware manufacturers and cloud providers to build UEFI firmware. UEFI is the software that starts a computer before the operating system loads. EDK II is widely used across the industry, including by major UEFI vendors such as AMI, Insyde and Phoenix. Even Microsoft’s more secure version, Project Mu, used the vulnerable component. “EDK2 contains a vulnerability in BIOS where a user may cause “Out-of-bounds Write”, Classic Buffer Overflow, and “Incorrect Calculation of Buffer Size” by remote access. Successful exploitation of this vulnerability can lead to arbitrary code execution. It could also impact Confidentiality, Integrity, and Availability.” reads the advisory. The flaw can corrupt memory in a component that handles ICMP messages, which devices use to report network errors. Attackers could exploit it to run code before the operating system starts and before security protections such as Secure Boot are fully active. Secure Boot checks that the software loaded during startup can be trusted, while the Trusted Platform Module (TPM) supports security functions such as hardware-based trust. Although the attacker’s code does not remain active after execution, it could help attackers install other malicious components that run early in the boot process. The flaw is a 16-year-old buffer overflow in the PXE-Base Code driver (NetworkPkg/UefiPxeBcDxe). That driver lets servers, storage gear and other devices boot from code downloaded over a local network. While it does that, it listens for ICMP errors, and it never enforces the 504-byte limit on how much it copies. “While a machine is PXE-booting over IPv4 or IPv6, an unauthenticated network attacker who can deliver ICMP error messages to it can corrupt DXE-phase memory and execute arbitrary code before the operating system loads, before Secure Boot or measured boot has verified or measured any OS component.” states the advisory. A malicious insider, or a hacker with low-level access to the local network, can send an error message that spills code past the limit and corrupts the UEFI module running on the CPU. The advisory is more precise. The driver keeps a receive request open for ICMP errors and copies each message into a fixed 504-byte field called Mode.IcmpError. In both the IPv4 and IPv6 handlers (PxeBcIcmpErrorDpcHandle and PxeBcIcmp6ErrorDpcHandle) the bounds handling is wrong: a longer message still gets copied, and the destination pointer moves by the cumulative length and not the per-fragment length. So an oversized message writes attacker-controlled bytes past the field, and nothing earlier on the receive path limits its size. The attack is simple. The attacker sends a direct message to the target’s IP address during the PXE boot process, even from a remote network. Sending invalid data can stop the boot process and cause a denial of service. If the attacker knows the target’s firmware version, they can create a fake event to run their own code at ring 0, the CPU’s highest privilege level. This also bypasses attestation, which uses cryptographic checks to prove that the hardware is trustworthy. As a result, the attack can help an attacker turn limited access into full control. The attacker needs some control over the local network. This could be an insider or an external attacker who already has a foothold in the target network and is seeking to gain higher privileges. So far, there’s no evidence that this flaw can be exploited to gain initial access to a network from the outside. The flaw affects some systems that start up over a network using EDK2-based firmware with PXE enabled. Home and small-office users, and anyone who boots only from a disk drive, aren’t affected. Researchers planned to disclose the bug in January, but AMI published a fix last month, revealing details of the flaw. TianoCore then issued a public warning. Attackers can now study the fix to develop exploits, while updating firmware across many devices could take a long time. It’s still unclear which devices are affected. Intel and Arm say their own products aren’t directly affected, but manufacturers may add vulnerable code. Several other companies hadn’t answered questions when the article was published. Organizations should contact their system or firmware supplier and disable network boot where possible. They should also monitor logs for suspicious activity. TPM and Secure Boot remain useful protections, but they don’t stop this attack. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, CVE-2026-97631)
Adobe has released patches to address multiple critical security flaws in Campaign Classic that, if successfully exploited, could result in arbitrary code execution, security feature bypass, and privilege escalation. The list of eight vulnerabilities is as follows - CVE-2026-104351 (CVSS score: 9.9) - A code injection vulnerability that could lead to arbitrary code execution.
Modern phishing campaigns can compromise American businesses without relying on traditional credential theft. Attackers can abuse legitimate cloud services, authentication mechanisms, and trusted business workflows to gain access to corporate accounts while leaving fewer obvious signs behind. ANY.RUN's analysis of Skyw4lker, a device code phishing campaign primarily targeting U.S. organizations
Background Network-connected surveillance cameras are now widespread in both home and enterprise environments, so securing them is essential to safeguarding physical spaces and sensitive assets. As these devices continue to gain new features and network connectivity capabilities, vulnerabilities in their implementation can have significant security implications. During our research, we discovered a denial-of-service vulnerability that affects Intelbras IP cameras systems. The flaw resides in a firmware update endpoint that is accessible without authentication and allows anyone with access to the local Wi-Fi network to knock cameras offline. A single request disrupts the camera for only about a minute, but sending periodic requests keeps the device offline indefinitely. We reported the issue to Intelbras, monitored the remediation process, validated the fix in the new firmware, and will now demonstrate the exploitation procedure step-by-step. Following our notification, Intelbras patched the vulnerability and released updated firmware (R.260804) along with update instructions. A candidate ID of CAN-2026-2035970 has been assigned by MITRE following submission, pending the final CVE assignment. Additionally, the Intelbras team recently informed us that MITRE has classified the vulnerability as Medium, assigning it a score of 5.1 under the CVSS 4.0 framework. The issue discussed in this article is no longer present in the latest firmware version. Firmware Intelbras provides firmware files on its official website. While users can manually install these updates via an SD card, the cameras also natively support firmware upgrades over the local network via their web interface and mobile app. We obtained the firmware version v240927 for the iM3B-C camera, which was the latest available version at the time of our research. According to Intelbras, the same firmware is also compatible with the iMX C, iM4 C, iM5 SC, iME 360 C, and iM7+ FC models. Below, we can view the firmware version and the camera model used as an example. To provide context, we will explain how the camera’s authentication mechanism works and why it is relevant to accessing the camera’s endpoints. The main firmware component is an ARM binary named sonia, responsible for controlling the kernel drivers used by the camera hardware, authentication, and livestream recording, among other things. How authentication works The global.login RPC method handles authentication at the /RPC2_Login endpoint. First, the client, such as the mobile app or a custom script, sends the username and an empty password. The camera responds with an authentication challenge (a set of values to verify the password without transmitting it). This response returns a temporary session, the encryption type in the encryption field, a random value, and a realm (authentication scope). At this stage, a false response is normal and does not indicate a failed login, as the authentication process is not yet complete. Next, the client calculates the response password from the authentication challenge. It first generates an MD5 (username:realm:original_password) hash as the base. It then calculates a second MD5 (username:random:first_md5) hash, where first_md5 is the result of the previous step. To complete the authentication, the client sends this final result back to /RPC2_Login in a second global.login call, passing the username, calculated password, and temporary session ID. If the login is accepted, the camera returns true and a new, authenticated session. This session must be used for all subsequent RPC calls, including the camera’s other endpoints, for example, the one that reboots the device or those that expose sensitive information. Affected endpoint The affected endpoint is the firmware upgrade route http://<ip_address>/firmwareUpgrade_service/Demo, which lacks authentication checks; furthermore, it fails to verify whether the firmware is actually valid before initiating the upgrade process. This creates a serious issue because the upgrade requires the camera to reboot, and that is precisely when the problem occurs: the camera enters reboot mode and eventually shuts down, appearing offline to the user and anyone who has the camera registered on their device. PoC: vulnerability exploitation Now that we have outlined how the vulnerability works, we will use a Python script on an iM3B-C camera to exploit it for demonstration purposes. The exploit contacts the camera’s endpoint to upload firmware. Below, we can see sonia creating the endpoint responsible for the firmware upgrade. Next, the exploit will hit the endpoint and cause the camera to reboot. Consequently, mobile phones running the Intelbras app will lose connection with the registered device. Below, we can see the camera operating normally: the green light is on and the app is showing it is available for viewing. The camera is online After the exploit executes, we can see the effects: the camera goes offline and loses connection to the registered devices. The camera is offline The exploit is quite simple: it sends an HTTP POST request with the firmware, which causes the camera to accept the request and initiate the reboot process. It does not matter whether the firmware is original; the reboot process will start regardless. New firmware version After we notified Intelbras about this flaw in the endpoint implementation, the company contacted the OEM vendor. As a result, a new firmware version was released that requires authentication to initiate an update through this endpoint. Below, we can compare the new firmware, which validates cookies and session data, with the old firmware, which performed no authentication checks and proceeded directly to the update routine. Real risk An attacker can remotely trigger the camera firmware upgrade and reboot process without authenticating or supplying a valid firmware image. This may cause the device to go offline, which results in a denial-of-service condition preventing legitimate users from accessing live monitoring or managing the camera. The potential impact is significant due to the number of affected users. The Intelbras Mibo Smart app, which the company provides to connect and manage the devices mentioned in this report, has over 4,000,000 downloads. Brazil represents the largest user base, followed by Paraguay, Ecuador, Colombia, Argentina, Chile, Peru, Bolivia, Uruguay, and Venezuela. As a result, exploitation of this issue affects a large number of users. Takeaways This is a medium-severity vulnerability that Intelbras is already aware of. The issue has been addressed in a newer firmware release (R.260804 along with update instructions), which mitigates this attack vector. Because the vulnerability directly affects the availability and normal operation of the affected cameras, it is highly recommended that users verify the firmware version currently installed on their devices and update to the latest available version as soon as possible. Keeping the firmware up to date is an essential security practice, especially for internet-connected surveillance devices, as outdated versions may remain exposed to known vulnerabilities.
A Ukrainian national was sentenced to 70 months in prison for his role in Nefilim and Hive ransomware attacks targeting hospitals, government entities, and high-revenue businesses worldwide between 2018 and 2021. The sentence follows the extradition of 35-year-old Artem Aleksandrovych Stryzhak to the United States on April 30, 2025, after authorities arrested him in Spain in June 2024. "Artem Stryzhak is a prolific cybercriminal who worked with multiple ransomware groups to target U.S. businesses and hospitals," said Brett Leatherman, the FBI's Cyber Branch Operations Director. "These groups disrupted patient care and caused more than $100 million in losses. Today's sentence reflects the seriousness of Stryzhak's crimes and demonstrates the FBI's global reach and extensive network of international partners."
Three Japan-focused cyberattacks show how AI helps hackers scale operations, while exploiting old systems and weak security remains key. In autumn 2026, Japanese companies and other organizations reported a series of data leaks involving their web systems. On October 9, Japan’s National Cybersecurity Office issued a warning to businesses, while the head of the ruling party’s cybersecurity team described cyberspace as being in a “state of emergency.” Researchers at Trend Micro studied three attack infrastructures to understand how hackers use AI. Their findings show three different approaches, ranging from limited AI assistance to systems that use AI agents to manage almost an entire attack. The researchers looked at files that attackers left on servers anyone could reach. These included attack scripts, lists of targets, logs, and records of commands. The files showed attacks on organizations in Japan and other countries. But the researchers could not see the victims’ own logs or network records. So they could not confirm every break-in, measure the full damage, or say who was behind it. Attackers also like to claim more success than they really had. The researchers only counted a result as real when the evidence backed it up. The three cases show that AI does not play the same role in every cyberattack. “The cases differ along two dimensions: how much of the attack AI handled and how confidently we can establish its involvement.” reads the report. “Case A used AI to drive the entire workflow, which we confirmed. Case B was human-led, with confirmed AI assistance in planning and tool development. Case C showed high-confidence indications of AI use in a limited role, such as tool development. All three were active in 2026, and much of the activity preceded the previously published ARTEX reports.” Case A: AI agents managed the attack workflow. The researchers confirmed the use of CyberStrikeAI, an open-source penetration-testing platform built around AI agents. It handled reconnaissance, vulnerability checks, exploitation, data theft and reporting as part of a repeatable process. The platform split tasks among multiple AI agents. One record mentioned a credential-search agent in a system that used 44 agents. The platform could also generate Japanese content, including forms and fake login pages. Researchers identified at least 19 target organizations, including at least 16 in Japan. The system worked on several targets at once and kept traffic to each organization relatively low. This made the activity harder to detect by checking the logs of a single victim. Despite this automation, the platform rarely gained deep access to target systems. In many cases, it had no active session or web shell and showed no evidence of stolen data. The clearest intrusion started through an administration page that was publicly accessible on an old web system. The attackers did not need to exploit a newly discovered vulnerability. Case B: A human attacker used AI to plan and build tools. In this case, the operator made the main decisions but used a large language model to speed up planning and tool development. The researchers found an attack plan written by an LLM that targeted services providing AI and GPU resources. The attacker presented requests as authorized security testing to get around the model’s safety limits. The researchers say this was a false claim, although they did not publish the exact method. The attacker also targeted AI infrastructure, including platforms for AI workflows, data processing and model inference. The researchers believe the goal may have been to gain access to computing resources that could be used to run AI models cheaply. Some intrusions had serious consequences. In one case, the attacker gained control across several systems, including an FTP service, a database, an administrator account, a web shell and SSH access. The attacker also restored backdoors after they had been removed. In another case, a geographic information system server was exposed with default credentials. This provided access to hundreds of thousands of land and business records, as well as Windows credentials and email data. The evidence confirmed that information was downloaded. However, the researchers found no evidence that AI carried out these attacks independently. It helped the operator plan and build tools, while the actual work relied mainly on scripts, existing software and human decisions. Case C: AI played a limited role. Here, the operator appears to have used AI mainly to develop tools and scripts. The researchers found no evidence that it was involved in planning or managing the wider operation. They rated AI involvement as highly likely, but not confirmed, because they found no direct evidence such as prompts or API keys. The operator ran at least six campaigns in 2026, targeting exposed VPN devices and Oracle WebLogic servers. The targets included devices from Cisco, Citrix, F5 and Yamaha. In attacks against Yamaha RTX1210 routers, the operator did not exploit a product vulnerability. Instead, the attacker used credentials found in configuration files. These credentials provided direct access to internal corporate networks. The researchers also found signs that AI may have helped write some commands and scripts. These included unusually structured comments and emoji used as status markers. Such clues can support an assessment, but they cannot prove AI use on their own. Japan was the main target in all three operations, but attackers also targeted other countries and regions. All three used Simplified Chinese, but this does not prove they came from the same group or location. “Simplified Chinese was the working language in all three infrastructures. Japan was the largest target country, although the operators also pursued nearby countries and regions. Entry points were exposed legacy systems or weaknesses left in default configurations.” concludes the report. “Target selection was opportunistic across industries: the operators sought systems that were easy to attack from outside and acted on what they found.” The main difference was how AI was used. In one case, AI agents managed much of the attack and worked on many targets at once. In another, AI helped a human plan attacks and build tools. In the third, AI was mainly used to develop tools. AI helped make attacks faster and easier to scale, but attackers still exploited familiar weaknesses, such as outdated web systems, exposed admin pages, default passwords and poorly secured network devices. Researchers also found that AI tools sometimes reported planned actions as successful, making it essential to verify their results. AI can also help defenders discover vulnerabilities. However, researchers found no evidence that these three operations used AI-discovered zero-day flaws. Their attacks relied on known vulnerabilities and poor security settings. The report identifies six main priorities for defenders: Review public-facing systems. Identify old web applications and update them or isolate them if they cannot be secured. Protect administration pages. Check that management interfaces are not exposed to the internet without a clear need and strong access controls. Secure VPNs and network devices. Review configurations, remove default credentials and check for reused passwords. Protect internal AI services. Include AI workflows, inference services and GPU systems in asset inventories, and check whether they are exposed. Improve monitoring. Look for low-volume attacks spread across many targets, which may be difficult to spot in the logs of a single organization. Prepare for AI misuse. Organizations that use LLMs for work should train staff to recognize requests that falsely claim to be authorized security testing. These security weaknesses existed long before AI became widely available. AI simply helps attackers find and exploit them faster and across more systems. The time between discovering a vulnerability and using it in an attack may also become shorter. Organizations should install security updates quickly and apply temporary protections when patches are not available. Researchers still don’t know who was behind the three operations, whether they were connected or how much damage they caused. Further reports may provide more answers. “The attackers’ identities, whether the three cases share an operator, the full scale of the damage, and the AI models used remain unresolved. Our observations come from attacker-side files and still require confirmation from the affected organizations.” concludes the report. “We are considering further technical reporting on individual cases: AI-driven activity in Case A, AI assistance in Case B, and limited AI assistance in Case C. We will also continue working with the relevant organizations.” The main lesson is clear: AI can make cyberattacks faster and larger, but the basic security priorities remain the same. Organizations must identify systems exposed to the internet, strengthen access controls and detect suspicious activity before attackers turn a simple weakness into a serious breach. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, Italy)
An unreleased Anthropic AI model found security flaws in Chrome, Safari, Android, Windows, and Linux and chained them into working proof-of-concept exploits, the company said in its latest report. The exploits were built in the lab after the model was prompted, not seen in any real attack, and Anthropic reported every flaw to the vendor first, so all of them are already patched. One proof of
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