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Malicious actor
Backdoors Cyber Security Exposed Servers Hacker attack Hacker group Malicious actor

Head Mare Hackers Exploit TrueConf Servers to Spread Backdoors Through Malicious Updates

 

The Head Mare hacktivist group has been targeting unpatched True Conf video conferencing enterprise servers to replace legitimate client installers with malware-containing versions, Kaspersky said. TrueConf is a business communication tool popular in Russia among enterprises and government agencies as an on-premise alternative to western video conferencing products like Zoom and Microsoft Teams. 

Kaspersky researchers discovered the attacks in July and identified that Head Mare hackers used TCP port 4307, which is open by default, to connect to the target TrueConf servers without authentication, and exploit the vulnerabilities KLCERT-26-057 and KLCERT-26-058, which have been tracked by KLCERT. They allowed the attackers to run a malicious script in an isolated TrueConf environment, bypass the sandbox and execute commands on the underlying operating system. 

The attackers then elevated their privileges to NT AUTHORITY\SYSTEM and replaced the \public\js\locale.php file with a web shell, which provided persistent remote access to the compromised server. Kaspersky said that Head Mare uses the web shell to collect sensitive information and access the TrueConf database and replace the legitimate TrueConf Client installer on the server with a malicious version containing the PhantomCore backdoor. 

When members of an organization connect to a compromised local TrueConf server, they can receive the trojanized installer as an update. Kaspersky also warned that employees could be exposed even if their own organization does not use TrueConf. Employees connecting to compromised TrueConf servers operated by counterparties to participate in online meetings can download infected installation packages. Head Mare also deploys PhantomGraph, another backdoor consisting of two dll files: SysExcSvc.dll and SysReadSvc.dll. 

The malware is capable of receiving commands through a Microsoft OneDrive account, executing these commands and returning the results. Observed activity comprised extracting the memory of the Local Security Authority Subsystem Service (LSASS) process to extract credentials, conducting reconnaissance by executing commands such as hostname and whoami, and establishing a reverse SSH tunnel. Kaspersky said that it is observing multiple active Head Mare campaigns targeting Russian organizations in instrumentation, electronics, transportation, energy, IT and software development. 

The group has used phishing, exploitation of public facing web servers and access through contractors as initial access methods. The exploited TrueConf vulnerabilities affected versions 5.3.x before 5.3.9, 5.4.x before 5.4.9 and 5.5.x before 5.5.5, as well as older versions. TrueConf fixed the vulnerabilities in versions 5.3.9, 5.4.9 and 5.5.5, which were released on June 18. 

The attacks followed another campaign reported by Check Point Research in April 2026, in which hackers exploited a zero-day arbitrary file execution vulnerability in TrueConf, tracked as CVE-2026-3502, to compromise users through trojanized client updates.
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vulnerabilities and exploits
China Linked Threats FBI Hacking Lumen security QScan QTFY vulnerabilities and exploits

FBI Disrupts QTFY Hacking Network Targeting U.S. Organizations




The U.S. Department of Justice (DoJ) and Federal Bureau of Investigation (FBI) have disrupted two hacking platforms operated by a China-linked threat group that were used to conduct reconnaissance, compromise vulnerable systems and conceal attacks against U.S. government agencies, critical infrastructure and other sensitive organizations.

The platforms, QScan and QTRouter, have been attributed to QTFY, a Chinese state-sponsored hacking group linked to Nanjing Xinjiuwei Network Technology Company. According to U.S. authorities, QTFY activity has targeted organizations including NASA, the Federal Reserve, Department of Energy, Department of Justice, Department of Health and Human Services, National Institutes of Health and the U.S. Senate.

Lumen Black Lotus Labs, which tracked the infrastructure for more than 18 months, said QTFY activity dates back to at least May 2018. The researchers described the group as an infrastructure "quartermaster" that developed reusable systems for reconnaissance, exploitation and traffic obfuscation.


QScan automated reconnaissance and exploitation

QScan formed the reconnaissance component of the operation. The platform scanned internet-connected systems and IoT devices for vulnerabilities before automatically compromising susceptible devices and incorporating them into the QTRouter network.

The FBI said QScan was also used to identify vulnerabilities in victim networks. Its infrastructure included servers responsible for distributing scanning tasks to worker nodes and collecting completed results.

The scale of the operation allowed QTFY to conduct reconnaissance across large numbers of systems. Lumen identified scanning activity spanning more than 130 countries, with targets including government, defense, aerospace, healthcare, financial, energy and research organizations.


QTRouter concealed attackers' origins

Compromised devices identified through QScan were subsequently used by QTRouter as proxy nodes. The network combined hacked IoT devices with commercial proxy services and leased virtual private servers (VPSs), allowing malicious traffic to pass through multiple intermediary systems.

This architecture made an intrusion originating from China appear to come from an internet connection located elsewhere. In some cases, QTRouter could route traffic through systems geographically close to the targeted organization, making the activity appear more consistent with legitimate local traffic.

QTRouter operated on routers running customized OpenWrt software and used the Clash proxy framework to establish connections. Operators could select available nodes and chain them together, creating multiple layers between themselves and their targets.

The FBI said this combination of compromised IoT devices and legitimate commercial proxy infrastructure made malicious traffic difficult to distinguish from normal internet activity.


Attackers exploited new and older vulnerabilities

QTFY's attack chain involved both recently disclosed and long-standing vulnerabilities. The vulnerabilities identified by investigators included flaws in Ivanti Connect Secure, Fortinet SSL-VPN, Citrix ADC, Microsoft Exchange Server, F5 BIG-IP, Kentico CMS, Apache Log4j, Atlassian Confluence, Check Point Quantum Gateway, CrushFTP and BeyondTrust Remote Support.

After obtaining initial access, QTFY actors used remote access trojans, web shells and legitimate credentials to maintain persistence.

The infrastructure could subsequently provide concealed access into victim networks through nearby compromised IoT devices. QTBotnet also allowed operators to control infected systems, execute commands and conduct distributed denial-of-service attacks.


Four-part infrastructure supported QTFY operations

Lumen identified QScan and QTRouter as part of a larger architecture that also included Fast Labyrinth and QTProxy.

Fast Labyrinth incorporated commercial proxy infrastructure into encrypted relay paths, while QTProxy managed operational nodes and allowed operators to configure routes toward selected targets.

The researchers compared the architecture to an operational relay box, or ORB, network. Such systems use compromised devices and leased infrastructure as rotating relay points, making traditional IP blocklists and location-based defenses less effective.

Lumen said the infrastructure demonstrated an increasingly industrialized model of China-linked cyber operations, in which reusable and shared services can provide reconnaissance and anonymity at global scale.


FBI seized domains used by the platforms

The disruption targeted domains hard-coded into QScan and QTRouter, including infrastructure used to distribute scanning tasks and administer proxy connections.

By seizing these domains through court-authorized action, U.S. authorities disrupted communication between the platforms and their operators, causing the systems to cease functioning.

Investigators also linked QTFY to Chinese cyber-brokering networks where exploits, malware and access to compromised organizations were allegedly traded. Nanjing Xinjiuwei was described by U.S. authorities as an enabling company with relationships across China's cyber ecosystem and connections to former People's Liberation Army personnel.

QTFY activity reportedly continued into June 2026, when actors targeted a U.S. election system.

The disruption demonstrates how China-linked threat actors are increasingly relying on distributed infrastructure rather than fixed attacker-controlled servers. While domain seizures can interrupt an operation, the reuse of compromised IoT devices, commercial proxies and leased servers means defenders will need to monitor behavior and network relationships rather than rely solely on static IP-based blocking.

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Threat Intelligence
Codenames Cyber Security Google Threat Groups Threat Intelligence

Google’s New Codename System Aims to Clarify Hacker Group Tracking

 

Cybersecurity companies have spent years giving hacking groups their own names so researchers and defenders can talk about them clearly. But the system has become crowded and inconsistent, because different organizations often label the same group in different ways.

Google recently changed its own naming approach to make that mess easier to navigate . Instead of long strings like APT numbers, its new method uses a memorable first name and a second word that signals a country of origin, such as Castle for China, Ion for Iran, Neptune for North Korea, and Relic for Russia. The goal is to make the labels easier to remember while still preserving useful context. 

Shane Huntley, who leads Google Threat Intelligence Group’s hunting work, said the change was needed because the number of threat groups has grown far beyond what researchers expected in the early 2010s. Google now tracks more than 5,000 activity clusters across several countries, which makes organization and communication much harder. Huntley also said the purpose of naming groups is practical: defenders need a baseline understanding of who is attacking, how they operate, and what they have done before.

That kind of background can help a company respond faster during a breach . If security teams recognize a known actor’s patterns, they can prepare defenses, narrow investigations, and respond with more confidence . The Lazarus Group, a North Korean state-backed hacking outfit, is one example of how earlier intelligence helps defenders identify likely goals and methods. The challenge is that not all threat actors behave the same way.

State-sponsored groups are often easier to follow because their targets and tactics are more consistent, while cybercriminal gangs may split apart, change members, or shift direction. Spyware makers and hackers-for-hire can also be difficult to track because they may work for many clients in many regions . Huntley argues that no company has perfect visibility, which is why naming systems will likely remain imperfect even if Google’s new scheme is simpler than before.
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Phishing As A Service
Activation Lock AI Voice Scam AnonyMousKIT Apple ID Theft Apple Phishing Apple Support Scam Cyber Fraud Phishing As A Service

Fake Apple Support Agents Target Stolen-Device Owners in Credential Scam


Using AI-powered voice calls and phishing messages, a new phishing-as-a-service platform targets owners of recently stolen Apple devices to obtain device passcodes, Apple ID credentials and two-factor authentication codes. 

In response to SOCRadar Threat Research Unit (STRU) research, security researchers have identified AnonyMousKIT as a credit-based service designed to assist criminals in defeating Apple's Activation Lock. By using this platform, attackers can communicate with their victims via email, SMS, WhatsApp, recorded calls, and artificial intelligence-generated voice agents posing as Apple Support representatives. 

AnonyMousKIT also makes the contact appear legitimate by utilizing information tied to the stolen device. By providing a serial number or IMEI to the platform, attackers can identify the device's model and determine whether it is currently in Find My. Victims can be directed to Apple-branded pages with an animated map showing the location of the device reported. 

People whose devices have recently been lost or stolen are more likely to actively check for their whereabouts as a result of these campaigns. By providing accurate device information and describing the circumstances surrounding the theft, attackers can increase the likelihood that the communication is a genuine notification regarding recovery or support. 

In most cases, the campaign seeks a device's passcode, followed by Apple ID credentials and an Apple 2FA code. Apple's support guidance states that legitimate representatives do not request passwords, device passcodes, or 2FA codes. With anonymousMousKIT, customers are permitted to choose from a variety of methods for contacting victims through a credit-based model. 

Email campaigns cost 1.50 credits, recorded voice calls cost 1 credit, and artificial intelligence voice agents cost 2 credits. A single set of stolen-device details can also be used for SMS and WhatsApp, allowing attackers to take multiple approaches to the same victim from a single set. Researchers identified the operation as more than just a conventional phishing kit, describing it as similar to a subscription-based criminal service, with credit packages, pricing tiers, customer support, and mechanisms for replacing compromised infrastructure. 

A stolen iPhone can have a number of consequences in addition to unlocking it. An attacker may be able to access the information stored in the account, including iCloud backups and other credentials, if he or she obtains the associated Apple ID credentials and 2FA code. Additionally, SOCRadar found coding errors within the platform that exposed links between multiple domains and backend installations, providing researchers with additional insights into the operation's infrastructure. 

With the AI voice component, SOCRadar was able to locate 200 call records and 55 transcripts related to the commercial voice platform Vapi which provide a closer look at the social engineering process. The callers appeared as “Alice” from Apple Support, and were able to use five voice personas across English, Spanish and Brazilian Portuguese.

Call recordings were collected between August 31, 2025, and May 30, 2026. 179 of 200 calls were directed to Brazilian telephone numbers. The fake support agent confirms ownership of the device before requesting the four- or six-digit passcode of the device in the reviewed conversations. After repeating the digits for confirmation, the agent claims to have been contacted by an Apple Store regarding an Activation Lock issue. 

The conversation then moves to the recovery link that was supposedly sent via text message. As determined by the recovered records, the voice operation was relatively inexpensive to run, with all 200 calls requiring approximately $19.24 per call. However, the available data does not indicate how many victims actually surrendered their passcodes, Apple ID credentials or 2FA codes. 

Among the recorded calls, 100 ended when the recipients hung up, 48 timed out due to silence, 24 did not receive an answer, and 28 ended because of platform errors or busy signals. The researchers also discovered that the call records had been retrieved due to an accessibility flaw in the platform's codebase. 

Two file paths exposed through the shared code enabled unauthenticated access to files stored in the web root, enabling the recovery of call logs and transcripts. Since the vulnerability was inherited by deployments based on the same codebase, it provides valuable insight into the broader infrastructure supporting AnonyMousKIT.

AnonyMousKIT demonstrates a structured criminal supply chain rather than a standalone phishing campaign, according to SOCRadar. Developers of the platform build and sell it, customers license the platform through storefronts, and operators use those services to conduct phishing campaigns. In addition to outsourcing the credential-harvesting process, criminals can concentrate on resale of stolen devices while criminals with limited technical expertise can perform the credential-harvesting process.

Activation Lock represents an important threat to criminals who steal devices. Once Find My is activated, an iPhone remains associated with its owner's Apple ID even after a factory reset, which creates a broader threat. 

By obtaining the account credentials and verification codes, attackers are able to defeat a security mechanism that otherwise makes activating and reselling stolen devices difficult. At the conclusion of SOCRadar's investigation, AnonyMousKIT was still active, emphasizing the increasing use of automated services to target stolen devices. According to the operation, criminals have been able to steal credentials from lost or stolen iPhones by combining stolen data, phishing and artificial intelligence. 

Apple accounts that have been compromised can expose data far beyond the device itself, posing a significant security risk to those who receive them.
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US police department
camera data Cyber Fraud data misuse Flock Cameras Flock Safety surveillance system US police department

US Police Officers Face Arrests and Firing for Misusing Flock Camera Data

 


Police officers across the United States are facing arrests, firings and investigations for allegedly misusing Flock Safety's automated license plate reader system to track people for personal reasons, including romantic partners, former partners and colleagues.

Flock operates more than 120,000 cameras across over 6,000 US communities, with the system recording around 20 billion license plate scans each month. The cameras are designed to help law enforcement locate stolen vehicles, identify vehicles connected to investigations and assist in finding missing people. However, their growing deployment has raised concerns about how much vehicle-movement data police can access and whether agencies are adequately monitoring that access.

A Washington Post analysis found that at least 50 law enforcement officers had been accused or charged with using license plate readers for unauthorized purposes. Flock systems were involved in 46 of those cases, while 26 involved officers allegedly using the technology to monitor women, including current or former romantic partners. The Institute for Justice has separately documented dozens of similar cases nationwide, with many occurring since 2024.

One of the most prominent cases involved former Braselton, Georgia, Police Chief Michael Steffman. According to The Washington Post, Steffman used Flock searches to monitor the movements of his former girlfriend and her daughter roughly 600 times. He was arrested on stalking, harassment and license-plate-reader misuse charges but died before his case went to trial.

Georgia has continued to see cases involving alleged misuse. Habersham County Deputy Christian Brewer was fired and arrested after an internal audit reportedly found that he had used Flock data to track someone with whom he had a personal relationship. A second Habersham County investigator, Jonathan Thomas, was arrested this week following another internal investigation into alleged misuse of the system.

The problem is not limited to Georgia. In Texas, former Lufkin police officer Zachary Anthony Klein was indicted on 100 felony counts after allegedly conducting more than 45,000 Flock searches over approximately 200 days. One license plate was reportedly searched nearly 3,500 times. The department subsequently suspended its use of Flock while investigations continued.

The Institute for Justice's database has continued adding cases in 2026, including allegations involving officers in Florida, Illinois, Georgia, Texas and other states. The database records incidents involving stalking, unauthorized searches and other non-law-enforcement uses of automated license plate reader data.

Flock says its platform records every search and provides audit tools intended to identify unusual activity. The company has also introduced additional safeguards, including mandatory case codes, stronger audit mechanisms and a recommended reduction in data retention from 30 days to seven days.

Critics argue that logging searches is only useful if police departments actually review those records and investigate suspicious activity. In several documented cases, alleged misuse was discovered only after victims or outside investigators identified unusual searches.

The issue has now expanded beyond individual officers. At least 69 alleged misuse incidents have been identified nationwide, while communities are increasingly questioning whether extensive vehicle surveillance can be deployed without stronger controls over retention, access and data sharing.

Residents have also begun investigating the system themselves. Have I Been Flocked allows users to check whether their license plate appears in publicly obtained Flock search records. The service has reportedly compiled more than 242 million recorded searches from audit logs obtained through public-records requests.

As Flock's network continues expanding, the controversy is shifting from whether automated license plate readers can help police solve crimes to a more difficult question: who watches the people given access to the surveillance system?

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Data server
Child Online Safety Child Privacy children data exposure Chinese Hackers Cyber Security data security Data server

39 Child Tracking Brands Linked to One Chinese Server, Exposing 45 Security Vulnerabilities

 

GPS trackers for children may put the tracked individuals and the people tracking them in danger, according to an investigation presented at the Black Hat security conference. Vangelis Stykas, CTO of Kumio, and Felipe Solferini, principal AI security engineer, discovered that 39 different consumer brands of parental monitoring devices share the same server in China where the data stored on them are processed. 

The researchers named the producers of the technologies, which the mentioned companies used in their devices, SeTracker, SinoTrack and TKStar. They found 45 different vulnerabilities that could allow unauthorized access to children’s smart devices enabling eavesdropping, video surveillance, and total remote control of the system where valuable information is stored. The researchers stated that to perform all these actions, a hacker would need only a free account on any of these platforms. 

The scientists also found that parental monitoring devices of different brands did not have the necessary authorization restrictions, which allowed accessing their systems freely. These devices could collect and store much more personal information than monitoring their location. Some of them have the functionality to record the screen, as well as control the camera and microphone. Thus, the location of the tracked device, photographs and video, the child’s screen, the applications and websites he visits, and his personal information can be known to unauthorized people. 

At the beginning of the demonstration, the researchers showed how they managed to run a script on a children’s smartwatch, which, among other things, dialed a phone number and transmitted an audio signal without any notification on the displayed screen that the call had begun. The scientists emphasized that the experiment was carried out ethically, and they used devices provided to them for the investigation. Stykas and Solferini also discovered that attacks on the system could have been made two years before the investigation began. 

This indicates that, in principle, someone could have been able to track the child’s location and personal data without his knowledge. The researchers contacted the companies more than 30 times, but received no response. One unknown dealer, however, responded to the scientists, noting that he was helping them investigate and would forward the information to the manufacturer. Researchers have concluded that parental monitoring devices pose a serious danger to privacy and safety by possessing many vulnerabilities. 

The investigation demonstrated that the same server is used for different brands, and the lack of protection allows hackers to gain full control of the system and track all the child’s activities. The report also suggests giving up these devices, and for those parents who want to control their children’s devices, the scientists recommended using the built-in tools of the giants: Apple Screen Time, Google Family Link, and Microsoft Family Safety.
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surveillance software
Chinese spyware Commercial global cyber attacks LightSpy spyware malware surveillance software

LightSpy Spyware Expands Global Reach, Targeting Devices Across More Than a Dozen Countries

 

Cybersecurity researchers have uncovered new evidence suggesting that the Chinese-linked LightSpy spyware operation has expanded significantly, with infections and infrastructure now spanning more than a dozen countries, including the United States and several European nations.

A report from cybersecurity firm Arctic Wolf describes LightSpy as an increasingly sophisticated commercial surveillance platform whose capabilities appear to be offered to governments, military organisations and private companies. First identified in 2018 and previously linked to Chinese state-backed hacking activity, the spyware is now believed to be controlled by a single threat actor that provides the platform to multiple customers.

The researchers identified at least 117 servers associated with LightSpy across multiple countries. The infrastructure indicates that the operation has developed a much wider global footprint than earlier investigations had revealed.

LightSpy has also evolved beyond targeting individual operating systems. Its modular architecture reportedly allows it to compromise smartphones, Apple devices, Windows computers and Linux servers, while newer versions have introduced the ability to target internet routers.

The router capability represents a particularly concerning development because compromising network equipment could allow attackers to observe or potentially access several devices connected to the same network. Arctic Wolf said some of the compromised routers are associated with NATO member countries, although it did not disclose the specific organisations involved.

The latest versions of LightSpy reportedly offer extensive surveillance capabilities. Once installed, the spyware can collect sensitive information such as precise location data, chat conversations, stored passwords and screen recordings. It can also remotely delete files and potentially make compromised devices unusable, giving operators capabilities that extend beyond surveillance to data destruction.

According to Arctic Wolf, LightSpy's development reflects a wider commercialisation of advanced spyware. Capabilities once primarily associated with intelligence agencies and state-sponsored cyber operations are increasingly being packaged and sold to a broader customer base.

The researchers said LightSpy appears to be marketed as a commercial product, featuring customised branding, demonstrations and billing mechanisms designed for prospective customers. This suggests the operation may function as a structured surveillance business rather than being limited to a single espionage campaign.

Researchers also uncovered a potential link to a Chinese contractor through an operational mistake. According to Arctic Wolf, one of the spyware operators accessed the malware's administration panel and used their real name and office address while ordering Kentucky Fried Chicken. Investigators believe the incident provided an unusual clue that helped connect the infrastructure to its operators.

Despite the findings, several questions surrounding LightSpy remain unanswered. Arctic Wolf said the identities of the platform's customers, the total number of victims and the precise relationship between its operators and the Chinese government have not been publicly established.

The findings nevertheless underscore the growing sophistication and international reach of commercial spyware. As surveillance technologies become increasingly commercialised, advanced cyber capabilities are becoming accessible to a broader range of customers, extending the potential threat well beyond traditional state intelligence operations.

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Technology
Adversarial Clothing AI Surveillance Black hat Facial Recognition Technology

Black Hat 2026: How Special Clothing Could Trick AI Surveillance Cameras

 

AI surveillance is getting smarter, but a new Black Hat 2026 demonstration suggests clothing could also become a privacy tool. PCMag reported that hacker and SecKC founder Bill Swearingen showed how printed “adversarial patterns” may confuse facial-recognition systems and lower their confidence in detecting a person. 

The issue matters because modern surveillance does not just record video; it often analyzes it in real time. Facial-recognition and person-detection tools look for shapes, edges, and visual cues that help algorithms decide whether a face or body is present. Swearingen’s idea is to inject visual noise into that process so the system misreads what it sees, even though a human observer would just notice an ordinary scarf or shirt. 

At the center of the project is a simple but powerful problem: machine vision can be tricked. According to PCMag, Swearingen created an algorithm that generates patterns designed to disrupt detection models, and he suggested those patterns could eventually be printed on fabric for everyday wear. In related coverage, the project was described as working against multiple computer-vision systems, not by hiding someone from the camera, but by preventing the software from reliably flagging them as a target. 

Still, the technology is not ready to be treated as a guaranteed shield. PCMag noted that the concept has only been proven digitally so far, not in real-world physical fabrics under normal conditions. That means lighting, camera angle, movement, garment fit, and software updates could all change the result, so a pattern that works in a demo may fail in daily life. 

Even with those limits, the experiment highlights a bigger debate about privacy and surveillance. Supporters see anti-surveillance clothing as a low-tech, wearable form of resistance that does not require batteries or devices. Critics, however, argue it may become an arms race, where surveillance companies retrain their models to ignore the patterns and reduce their effectiveness over time. The broader issue is that public anonymity is becoming harder to preserve as AI systems spread, and people may increasingly look for creative ways to stay untracked.
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Vulnerability Management
AI Code Security AI Coding Risks Cyber Security Dependency Security Open Source Security Remediation Debt Secure Software Development Software Supply Chain Security Vulnerability Management

Enterprise AI Coding Adoption Fuels Open-Source Security Debt


As artificial intelligence coding tools are rapidly adopted, development teams are able to develop software more quickly, however, cybersecurity teams are also becoming increasingly under pressure due to the increasing volume of AI-generated code. Open-source dependencies have become increasingly common, and their rapid introduction can result in increased vulnerabilities for an organization and additional remediation workloads. This is a key concern. 

A study involving 300 security and engineering leaders in technology, financial services, healthcare, manufacturing, and government sectors revealed the growing challenges associated with managing this risk. Organizations may face remediation debt if dependencies accumulate faster than security teams can assess and resolve them, which could adversely affect security operations, compliance, productivity, and overall business resilience. 

AI coding systems are expected to become increasingly autonomous as time goes on, resulting in software and dependencies being introduced into enterprise environments at a pace that existing security processes may not be able to keep up with. Prioritization is also becoming increasingly important in light of the growing number of vulnerabilities. If every CVE is treated equally, security resources will be consumed rapidly without addressing the weaknesses that are most significant. 

There are several factors that can be considered in determining which issues require immediate action, including whether the vulnerability is reachable, whether the flaw can be exploited, and which systems or data will be impacted. Security controls are also becoming more involved in software development earlier. Testing static applications for security and analysis of software composition can be incorporated into development environments and continuous integration/continuous delivery pipelines to identify vulnerable dependencies and insecure code before the release process progresses further. 

By following this approach, security teams are less likely to discover large volumes of unresolved issues when development has been completed. AI-assisted development is becoming increasingly reliant upon dependency visibility. 

Software bills of materials can provide a comprehensive inventory of components used across applications, while controlled package sources and dependency policies can prevent libraries with known vulnerabilities from entering the development environment. It is also necessary to clearly define who will be responsible for clearing this backlog. 

Creating remediation deadlines based on risk level and assigning vulnerabilities to development teams responsible for the affected code can assist in making the process more measurable. Creating and verifying tickets as well as completing fixes automatically can also contribute to preventing vulnerabilities from remaining unresolved after they have been identified. The security backlog itself is not the only challenge that AI-assisted development can present when engineers approve code generated without understanding the design or underlying assumptions. 

In the event that the generated code becomes part of critical application logic, such gaps in understanding can make it more difficult to make later changes and troubleshoot. Increasing volumes of artificial intelligence-assisted development are putting additional pressure on existing vulnerability management methods. 

Generated code may bring in open-source libraries and transitive dependencies that may not be examined as thoroughly as manually selected components. These dependencies can result in a steady buildup of vulnerabilities that require assessment and remediation, which may cause security teams to face a steadily increasing backlog. 

Counting CVEs alone cannot provide a reliable indication of actual risk. There may be more urgent urgency for issues with limited exposure when they affect application components, are exposed to untrusted input, or are associated with active exploitation. The business impact of an issue also plays a role in determining which findings should be addressed first, as well as which findings should be addressed first. 

Security validation is therefore becoming increasingly integrated into the development process. Identifying insecure code and vulnerable dependencies before they reach production can be accomplished by integrating static application security testing and software composition analysis into development workflows and Continuous Integration/Continuous Delivery pipelines. The implementation of this approach can reduce the amount of remediation work that must be done by security teams following deployment. 

Greater visibility into software components is also of importance. A software bill of materials can provide information about the open-source packages that are used across various applications, while controls around approved package sources can help prevent known vulnerable or unsuitable dependencies from entering development environments. Additionally, it is necessary to clearly define ownership of the remediation process itself. 

By assigning vulnerabilities to teams responsible for the affected code and establishing a risk-based remediation timeline, and verifying the fixes, organizations can prevent unresolved findings from building up as AI-driven development continues.

In order to ensure successful software development, organizations will need stronger visibility, risk-based vulnerability prioritization, and security controls throughout the development process. A strong focus on dependency management and remediation work can assist in preventing the growth of security debt from becoming a larger risk for the software supply chain.
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OT Security
Black Hat 2026 Critical Infrastructure Cyber Attacks CISA OT Security

Hackers Shift From Disrupting to Destroying Critical Infrastructure

 

Cyberattacks on operational technology (OT) systems have shifted from data theft and ransom demands toward outright physical destruction, according to experts speaking at the Black Hat USA cybersecurity conference in Las Vegas. This trend poses a serious threat to critical infrastructure operators, many of whom are already underfunded and understaffed while managing aging industrial equipment amid heightened geopolitical tension. 

From espionage to physical sabotage 

Cheri Benedict, a cybersecurity and supply chain adviser at the White House's Office of the Federal Chief Information Officer, said OT attacks are increasingly targeting physical operations rather than just data. Matthew Rogers, the operational technology cybersecurity lead at CISA, echoed this concern, noting a "real desire and willingness to cause this impact at scale". Recent Iran-linked intrusions into U.S. water systems have failed to compromise drinking water safety, but Iran has also worked to disable safety monitoring systems across water and other sectors—an escalation Rogers called "what should actually scare you". 

A CISA advisory updated on July 22 revealed that Iran-linked actors planted malware on a programmable logic controller that overrode instruction sets responsible for maintaining safe operating parameters. This tactic traces back to 2017, when malware called Triton disabled safety equipment at a Saudi Arabian power plant, marking one of the earliest known examples of this attack style. Because operators rarely inspect PLCs unless they malfunction, such malware can remain undetected for years, making each compromised controller what Rogers described as "a ticking time bomb". 

Wipers replace ransomware 

Neal Pollard, a partner at consulting firm Control Risks, said wiper malware has become more prevalent than ransomware in some cases, reflecting "a change in intent and understanding" among threat actors even as overall attack volume stays consistent. Rogers added that hackers are increasingly deploying code designed to permanently cripple industrial control systems, warning that the U.S. lacks sufficient replacement equipment to recover at scale from such destruction. 

The panel emphasized that longstanding weaknesses—default passwords, unpatchable legacy devices, and unencrypted communications—remain the primary entry points for attackers. Vu Nguyen, CISO at the Department of Justice, noted that isolated OT environments with limited connectivity make log collection and incident response especially difficult. Notably, Rogers said none of the recent malicious activity relied on a single CVE or advanced AI tools, since OT systems remain so vulnerable that sophisticated exploits simply aren't necessary.
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technology
ai agents apis business data consulting MCP Salesforce software technology

Salesforce’s Headless 360 Pushes Enterprise Software Beyond the Browser

 




Salesforce is preparing for a future in which employees may no longer need to open Salesforce to use it.

At TDX 2026, CEO Marc Benioff described the shift with the line, “Our API is the UI,” as the company introduced Headless 360. The platform makes Salesforce capabilities, including Customer 360, Agentforce and Slack, accessible through APIs, Model Context Protocol (MCP) tools and command-line interfaces (CLI), allowing applications and AI agents to interact with Salesforce without relying on its traditional browser interface. Salesforce says its Headless 360 MCP server can support operations including querying and updating records, managing permissions, working with Apex and interacting with platform events.

The change challenges a model Salesforce spent decades building: software operated primarily by humans through screens and sold largely through user-based licensing.

If an AI agent performs the work, the traditional per-seat model becomes harder to justify. An agent does not need a dashboard or training programme in the same way an employee does. It needs authenticated access to data, tools and workflows.

Salesforce is already experimenting with consumption-based pricing. Its Agentforce model includes Flex Credits, which customers can use for agent actions, alongside conversation-based and user-based pricing. Salesforce lists 100,000 Flex Credits at $500, while certain Agentforce services can also be priced according to successful outcomes.

That transition could also affect the Salesforce consulting ecosystem. Implementation work historically centred on configuring screens, workflows and processes for employees. As agents take over more workflows, organizations may instead spend more on data quality, permissions, API architecture, agent governance and testing.

Salesforce has a reason to disrupt itself before competitors do.

AI-native platforms can be designed around APIs and autonomous agents without inheriting the assumptions of traditional enterprise software. By opening Salesforce to agents, the company is betting that its strongest asset is not the interface but the business data, permissions and workflows underneath it.

That makes governance a central part of the strategy.

Salesforce's Einstein Trust Layer is designed to keep Agentforce grounded in enterprise data while respecting existing access controls. Salesforce describes capabilities including dynamic grounding, secure data retrieval, auditability and zero-data-retention arrangements with external model providers.

But making Salesforce accessible through MCP and external AI systems creates another risk: the company no longer fully controls the interface through which users interact with its platform.

A sales manager could eventually ask an external AI agent to analyse pipeline data, update opportunities, trigger Salesforce workflows and coordinate information across Slack, Salesforce and other enterprise systems. The AI layer becomes the operating interface while Salesforce functions as the underlying system of record.

MCP also introduces new security considerations. Research has identified threats including tool poisoning and prompt injection, where malicious instructions embedded in tools or outputs can influence an agent's behaviour. The U.S. National Security Agency has similarly warned about cascading prompt-injection risks in MCP environments, where one agent's output can become another system's input.

The pricing problem remains unresolved as well. Agent actions vary enormously in complexity. Updating a contact record is not equivalent to autonomously completing a sales renewal, making a simple “pay per action” model difficult to align with business value.

Salesforce's Headless 360 strategy therefore represents more than a move away from browsers. It is a test of what enterprise software is worth when humans are no longer its primary operators.

Interfaces can be replaced. What is harder to replace is trusted business data, permission architecture, proprietary workflows and the infrastructure required to let autonomous systems act safely.

Salesforce is betting that those foundations will remain valuable.

The risk is that by making them accessible to external agents, it could also help those agents become the new interface between enterprises and Salesforce itself.

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Vehicle Tracking
ALPR Surveillance Flock Cameras Flock Safety License Plate Readers Mass Surveillance Privacy Vehicle Tracking

Flock Cameras Spark Debate Over Surveillance and Civil Liberties


With Flock Safety operating one of the largest networks of automatic license plate readers (ALPRs), automatic license plate readers (ALPRs) are becoming more common across the United States as part of surveillance infrastructure. As a result of their rapid expansion, privacy advocates have expressed concern that such systems may create detailed records of vehicle movements in communities across the nation. 

How Flock Cameras Work

While traffic enforcement cameras usually focus on specific violations, Flock cameras photograph passing vehicles and translate the images into searchable records. License plates, locations, times, make, model, color and body type can all be included in records, along with distinguishing features such as bumper stickers or visible damage that can assist investigators in finding a particular vehicle or based on broader descriptions.

Watchlists are also available for cars associated with stolen vehicles, missing people, or criminal investigations, triggering alerts in the event that a potential match is detected. It is possible for participating law enforcement agencies to search the data of other agencies, depending on how their networks are configured. 

Why Police Departments Use Flock Cameras

A flock camera is a compact device that captures passing vehicles and records information such as license plate numbers, vehicle make and model, color, and location. Throughout the course of the investigation, data will be stored in a searchable system that will allow participating law enforcement agencies and other authorized organizations to access the system, potentially enabling the tracking of individual vehicle movements. 

The company claims that its technology does not utilize facial recognition and that customers can manage access to collected data through controls. However, given the extent to which its network is deployed, concerns have been raised about the manner in which vehicle data is shared, retained, and utilized. Approximately 120,000 cameras are now deployed across 49 states in the company's system, which is deployed by police departments, businesses, schools and homeowner associations in more than 6,000 communities. 

With the capabilities of the technology, more than just a license plate can be captured, as the records may include distinctive vehicle characteristics such as bumper stickers, dents, and other visible features. With the proliferation of surveillance cameras along public roads as well as private properties, questions regarding data access, civil liberties, and data privacy are becoming increasingly difficult to separate from the broader discussion surrounding public safety technology. 

Why Flock Cameras Are Controversial

It is not just about a single camera recording the movement of a vehicle that is of concern, but the network surrounding it at large. By using a large number of cameras, investigators may be able to reconstruct patterns of movement involving individuals who are not suspected of committing crimes by repeating recordings of the same vehicle at various times and locations. 

The use of vehicle-location data has also been criticized by privacy advocates, who have noted that it may reveal visits to sensitive areas, such as health facilities, protest sites, and churches. Searches based on historic ALPR records are still subject to legal uncertainty, including when warrants are required. Flock rejects the characterization that its system constitutes mass surveillance, however. 

Data Sharing Raises Additional Concerns

In addition to bringing Flock into the debate about immigration enforcement, data sharing has brought Flock into the public eye. According to a 2025 review of search logs, there were more than 4,000 Flock searches conducted by local and state police at the request of federal authorities, including searches that may have been related to immigration enforcement. 

An investigation conducted in 2026 revealed that outside police departments searched school cameras. It has been contested that the federal government has direct access to Flock's cameras, claiming it does not have a contract with U.S. Immigration and Customs Enforcement and does not have the right to access its data or cameras directly. 

Unauthorized Access and Personal Misuse 

In addition to allegations of misuse, there have been 28 documented cases in which officers are alleged to have abused license plate reader systems to monitor spouses, former spouses, colleagues, or romantic interests. 

Another instance occurred in July 2026 when North Carolina authorities arrested a Charlotte-Mecklenburg police officer who was accused of conducting an unauthorized license plate search for a non-law enforcement purpose using Flock and the state criminal justice database. 

Flock Cameras Can Also Produce False Alerts

If surveillance data is inaccurate, it can also pose problems. During June 2026, a driver in Minnesota was stopped by Flock alerts triggered by license plates that were similar to license plates reported stolen in another state. According to Flock, license plate translations are sometimes incomplete or inaccurate, which can result in negative consequences when automated alerts are used to influence police conduct. 

Communities Push Back Against Flock Surveillance

Over 80 municipalities have reported terminating or refusing to renew their Flock agreements, while Washington has imposed restrictions on how license plate data can be collected, searched, and shared as a result of the debate. 

Opposition to the technology has gone beyond policy debates. There have been at least 33 incidents in which Flock cameras have been damaged or destroyed, including cases where cameras have been painted, blocked, cut down, or burned in 23 states.
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Hardware Bug
Android Android Smartphone Android Softwares Cyber Security Google security Hardware Bug

Why Andy Rubin’s Essential Phone Failed Despite Fixing Android’s Biggest Problems

 

Andy Rubin spent ten years creating Android before launching Essential Products, which was based on the idea that Android phones had too many compromises, such as bloatware, software skins, slow updates, and accessories that became obsolete when new hardware was released. Essential launched the PH-1 in August 2017, which had near-stock Android, premium materials, fast updates, and a display that extended to the edges. 

Rubin had co-founded Android Inc. with Rich Miner, Nick Sears, and Chris White in 2003, and Google bought the company in 2005 for $50 million. Rubin continued to lead Android’s development for the next eight years. The PH-1 was meant to overcome some of the shortcomings of the open-source platform. It had Android 7.1.1 and was expected to receive two major Android upgrades and three years of monthly security updates. 

Essential delivered on Android 9 and Android 10, the same day as Google’s Pixel phones. The hardware was also supposed to overcome Android’s challenges. The phone had a titanium frame and a ceramic back, and it was among the first smartphones to have a notch. It had magnetic pins on the back, which were supposed to allow accessories to snap onto the phone instead of using a USB-C port. Essential announced a 360 camera and an audio adapter, but the ecosystem was never realized.

The launch of the PH-1 did not go well for Essential. The company announced that the phone would be available for purchase within 30 days, but the first units were not shipped until August 25 th , nearly two months after launch. The camera was also heavily criticized, and the $699 price was permanently reduced to $499 only two months after its launch. The only US carrier that sold the Essential PH-1 was Sprint. Essential’s sales were also underwhelming despite the star power of Andy Rubin.

A $300 million funding round in 2017 valued Essential at around $1.2 billion, but Bloomberg revealed that Essential had only sold 150,000 phones by May 2018. In October 2018, The New York Times revealed that Google had investigated a sexual harassment complaint against Rubin and found the allegations credible. Google approved a $90 million exit package for Rubin, but he denied the allegations. 

The report received a negative reaction from many Google employees, and Rubin’s reputation became a liability for Essential. Essential also announced Project Gem, a tall and thin smartphone that was designed to be used with one hand. The phone never reached the market, and Essential filed for bankruptcy on February 12 th , 2020, after realizing that there was no viable way to bring the phone to the market. The PH-1 was a lesson that high-end materials, limited software, and fast updates were not enough for a struggling smartphone brand to survive. 

The phone’s troubled launch, limited accessories, poor camera, and lack of network support hindered its chances, and Essential was unable to turn it around. The company realized that its ideas were not scalable enough to sustain a smartphone manufacturer, and it filed for bankruptcy later in 2020.
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Technology
AI Agent Security AI cybersecurity AI sandbox escape Microsoft Copilot security Microsoft Copilot vulnerability Technology

AI Sandbox Escape in Microsoft Copilot Raises New Concerns Over AI Agent Security

 

Security researchers are increasingly examining whether artificial intelligence can do more than accelerate existing cyberattacks and potentially develop entirely new methods of exploitation. A recently uncovered AI sandbox escape in Microsoft Copilot offers one of the clearest indications that AI environments could be exploited to reach systems and data beyond their intended boundaries.

Joe Hladik, head of Zero Labs, the threat research division of Rubrik Inc., has spent years studying backup data, an area he believes remains relatively overlooked by the cybersecurity industry. This year, his team expanded its research to examine how organizations and employees are using AI assistants, beginning with Microsoft Copilot, which is used by around 20 million people and approximately 90% of Fortune 500 companies.

“No one’s looking at backup data,” Hladik said. “We found it to be a viable place to find actual intelligence to act upon.”

Hladik discussed the research with Krista Case during Black Hat USA in an interview broadcast by theCUBE, SiliconANGLE Media’s livestreaming studio. The conversation focused on Rubrik Zero Labs’ discovery involving Microsoft Copilot and the broader security implications for AI-powered agents.

How the Microsoft Copilot sandbox escape worked

Rubrik Zero Labs discovered the vulnerability in February and subsequently followed responsible disclosure procedures by notifying Microsoft. According to Hladik, Microsoft addressed the specific vulnerability by the middle of March.

Although the particular flaw has been patched, Hladik said the research demonstrated a broader technique that could potentially be relevant to other AI copilots. The method involved escaping Copilot’s isolated environment and reaching Azure’s backend infrastructure.

Researcher Ori Lahav is presenting the detailed findings at Black Hat USA.

“[That] would allow you to get command and control of probably hundreds, thousands, or much more, depending on the volume of what exists within that tenant of users’ files, SharePoint files, OneDrive, whatever,” Hladik said. “It’s a major, major find.”

The discovery also highlights the potential scale of an AI-related security incident. If an attacker were able to move beyond an AI assistant’s sandbox, access to organizational resources could potentially extend across files and other information stored within an enterprise environment.

Organizations still lack visibility into AI agents

The Copilot discovery comes as businesses rapidly deploy AI agents without necessarily having complete visibility into where those systems operate or what they can access.

Research from Rubrik Zero Labs found that only 23% of security leaders have complete visibility into the AI agents operating within their organizations. Rubrik is attempting to address this challenge through new AI agent governance capabilities introduced this week.

Hladik compared AI agents with technologies security teams have encountered before, arguing that their underlying architecture is not entirely unfamiliar.

“Agents are just bots with models,” Hladik said. “They’re a bot that asks a model, and then the model will tell them what to do, and then they act. It’s new, it’s cool, but at the same time, I’ve seen this before.”

The findings underscore a growing challenge for organizations deploying AI: securing not only the models themselves but also thwe environments, permissions, data and connected services that AI agents can interact with. As businesses increasingly integrate AI assistants into everyday workflows, vulnerabilities that allow these systems to escape their intended boundaries could create significant new attack surfaces.


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Gaming Security
Age Restriction AI in gaming AI technology Children Privacy Cyber Security Data Privacy Data Privacy Concerns data security Gaming Security

Roblox Privacy System Tracks Data Across Hundreds of Systems as Platform Faces Child Safety Concerns

 

Roblox announces new federated central data coordination, but the system also acts as a reminder of the amount of data the company stores about its users and their activity on the platform As the platform boasts more than 132 million daily users, half of which are under the age of 18, Roblox has a large-scale privacy and safety issue. 

At the Black Hat security conference, Roblox engineering manager Hao Zhang and principal privacy software engineer Yiwen Luo spoke about the company’s approach to operational privacy and data deletion. One user request to delete data could trigger over 600 subtasks that need to be tackled by different teams and systems. According to Zhang, the entire system is complex and requires close collaboration between hundreds of systems; one of the biggest challenges was figuring out where exactly the data about the user is stored. 

Luo added that per the privacy policy, Roblox collects and stores most information about the user for as long as the account is active on the platform. The topics range from chat content, audio and video data, device information, and demography, to email and phone number, government ID and selfie for voice chat and other restricted content, payment information, and username, date of birth, and password. Roblox has experienced a 3.5X growth in year-over-year privacy-related user data requests. 

The new federated management system aims to handle such requests in a more efficient system-wide manner across the company’s systems and data platforms, as well as the third-party ones storing user data. Roblox is using artificial intelligence and other technologies to improve moderation, safety, and privacy on its platform. The company’s system, called Sentinel, is designed to detect harmful content and messages using machine learning algorithms. 

Roblox also relies on a combination of human moderation and automated tools to review and filter game catalogs, chat content, and other materials. It implements preventive algorithms and age-estimation solutions as a part of its safety measures. However, the growing use of tracking systems, tools, and the controversy around the age-verification laws in over half of the U.S. states have sparked debates regarding data privacy and potential risks to users’ safety and data privacy. 

The expansion of Roblox’s operations has also led to increased scrutiny from regulators. After the games containing violent and extremist content were leaked, and the lawsuits regarding the company’s alleged role in facilitating predation and grooming were filed, Roblox’s moderation capabilities and safety tools have come under the magnifying glass. The Roblox Sentinel documentation reveals that roughly 1,200 potential child-endangerment reports had been reviewed.

Still, there was no information about how many of those had been confirmed as actual cases. While the new federated security system allows Roblox to have more visibility and control over where the data about its users is stored and how does the company handles data deletion requests, its transparency around the matter is limited by the amount of data the company stores about its users and the extent to which it monitors its platforms.
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Muse Code
AI Tool Digital Privacy Meta Mobile Security Muse Code

Meta’s Muse Code: Affordable AI Coding with a Privacy Catch

 

Meta, the corporate umbrella behind Facebook, Instagram, and WhatsApp, has officially launched Muse Code, a new artificial intelligence system designed to assist developers in writing software. Announced by CEO Mark Zuckerberg via an X post, Muse Code functions as a “terminal coding agent” capable of handling complete software engineering tasks—from planning changes and writing code to validating results. This move reinforces Meta’s continued investment in AI, even as its public image remains tied to its 2021 metaverse pivot. 

What sets Muse Code apart is its ability to maintain context across a developer’s session. According to Zuckerberg, the tool runs specialized background agents that stay active throughout, learning a coder’s habits and preferred patterns. This means if a developer has previously generated a specific code fragment using Muse, the system remembers it for future reuse. Additionally, Muse dynamically allocates tasks: for complex requests, it “fans out” work to separate sub-agents operating in parallel within isolated worktrees, ensuring the original codebase remains untouched during experimentation. 

Despite its technical sophistication and cost advantage, Muse Code comes with a notable caveat: privacy. As with many AI-driven platforms, the tool’s ability to learn from user behavior and retain session data raises questions about how developer information is stored, used, and potentially shared. While Meta has not disclosed full details on data handling policies for Muse Code, the trade-off between affordability and privacy remains a critical consideration for enterprises and individual developers alike. 

Muse Code arrives amid Meta’s aggressive push into AI infrastructure and tooling. Zuckerberg has previously stated ambitions for AI to write most of Meta’s code within 12 to 18 months, and the company has reported a 30% rise in engineer productivity since early 2025, largely attributed to AI coding assistants. This launch also coincides with similar moves by competitors—Google recently unveiled Gemini 3.7 Flash, a low-cost AI model for coding workflows—highlighting a growing industry race to democratize AI-assisted development.

For developers, Muse Code represents both opportunity and caution. Its ability to reduce repetitive tasks, preserve work mid-crash, and scale complex projects could significantly boost productivity. However, the privacy implications underscore the need for transparent data policies and robust security measures. As AI coding tools become more prevalent, the balance between efficiency, cost, and data sovereignty will likely shape the next chapter of software development.
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Supreme Court
CBI Data Breach Data Governance Digital Personal Data Protection DPDP Act India Medical Data breach Supreme Court

Supreme Court to Hear Case Over 1.5 Lakh Medical Records Breach





The Supreme Court has issued notice on a petition seeking a Central Bureau of Investigation (CBI) probe into an alleged cyberattack that Vitraya Technologies claims resulted in the theft of medical, insurance and other sensitive personal information belonging to nearly 1.5 lakh Indian citizens.

A three-judge bench comprising Chief Justice of India Surya Kant and Justices Joymalya Bagchi and V Mohana agreed to examine the petition filed by Vitraya Technologies Pvt Ltd, a health-tech company that operates a technology platform for automating and settling health insurance claims.

The case places the alleged compromise of highly sensitive healthcare information alongside questions about the adequacy of the police investigation and the protection of informational privacy. The company has approached the court under Article 32 of the Constitution, arguing that the alleged breach has implications for the fundamental right to privacy protected under Article 21.

During the hearing, senior advocate K Parameshwar, appearing for Vitraya, told the court that the alleged intrusion affected data across six states and that the company had been approaching authorities since the incident was reported in 2025.

Parameshwar said Vitraya submitted its initial complaint in March 2025 but that an FIR was not registered until August 29, 2025. He also questioned why the case continued to name unknown persons despite the company claiming that it had supplied investigators with technical information concerning the suspected intrusion.

The counsel told the bench that Vitraya had also provided information concerning a server in Singapore to which the company's investigation allegedly traced medical records belonging to almost 1.5 lakh Indians.

The petition seeks transfer of the investigation to the CBI. In the alternative, Vitraya has asked the Supreme Court to order a court-monitored Special Investigation Team (SIT).


Alleged attack began with unauthorised access

According to the petition, Vitraya detected what it described as a coordinated cyberattack in February 2025.

The alleged activity included repeated brute-force login attempts against the company's systems, unauthorised access to its digital infrastructure, bulk downloading of confidential records and the extraction of sensitive customer information.

The data allegedly exposed in the incident includes medical records, health insurance claim information, Aadhaar-linked details and other personally identifiable information.

The combination of medical information with identity and insurance data makes the alleged incident particularly sensitive. Medical records can contain information about an individual's diagnoses, treatment history and health conditions, while Aadhaar-linked information can connect those records to an identifiable individual.

Vitraya's own platform is designed to handle this type of information. The company says its technology automates health insurance claims using artificial intelligence, machine learning, medical natural-language processing and blockchain-based smart contracts. It describes its platform as being used by more than 6,000 hospitals and says it processes approximately 10 million claims worth around $2 billion annually.

The company's technology infrastructure therefore sits within a data-intensive part of the healthcare and insurance ecosystem, where information can move between healthcare providers, insurers and technology platforms during the claims process.


Vitraya alleges attack was linked to rival companies

Following an internal forensic investigation, Vitraya claims that its security team identified suspicious IP addresses, server activity and other digital footprints that it says were associated with Remedinet Technologies Pvt Ltd and IHX Pvt Ltd.

The petition further alleges that these entities were connected to Bessemer Venture Partners and that the alleged activity involved Bessemer, Medi Assist, Perfios Software Solutions Pvt Ltd and other entities described by Vitraya as competitors.

These allegations have not been established by the Supreme Court. The companies named in the petition should not be treated as responsible for the breach unless an investigation establishes their involvement.

Vitraya says its forensic examination produced technical material that it subsequently supplied to investigators. The company claims this included server information, IP addresses, technical logs, details concerning the alleged actors and other documentary evidence.

The company approached Punjab's cybercrime authorities on March 5, 2025, according to the petition.

However, Vitraya alleges that its repeated representations and cooperation during the preliminary inquiry did not result in an FIR for almost six months.

The FIR was ultimately registered on August 29, 2025, at the Punjab State Cyber Crime Police Station in SAS Nagar. According to the petition, the case was registered under Sections 66 and 66B of the Information Technology Act and against unknown persons.

Under the IT Act, Section 66 addresses computer-related offences committed dishonestly or fraudulently, while Section 66B deals with dishonestly receiving or retaining stolen computer resources or communication devices while knowing, or having reason to believe, that they are stolen.

Vitraya has argued that the provisions used in the FIR do not adequately reflect the scale and complexity of the alleged incident. The company has also questioned why the FIR continued to identify the suspects as unknown despite the technical material it says had already been provided to police.


Company questions progress of investigation

The petition alleges that the investigation has not involved sufficient forensic examination or preservation of the digital evidence relevant to the alleged attack.

Vitraya claims that investigators have not undertaken substantial measures such as examining or seizing relevant digital infrastructure, preserving electronic evidence or conducting custodial interrogation of suspected individuals.

The company argues that these alleged shortcomings are particularly important because the incident involves systems and entities operating across multiple jurisdictions.

According to Vitraya, the alleged breach spans six states, involves multiple corporate entities and includes digital infrastructure located outside India. The company has specifically referred to a Singapore-based server where it alleges that the compromised medical information was transferred.

The cross-border element could complicate an investigation because digital evidence may be distributed across different jurisdictions, requiring investigators to establish where systems and data were located, identify the parties controlling those systems and preserve evidence before it can be deleted, altered or moved.

The company therefore argues that the investigation requires an agency with the technical capacity and jurisdictional reach to examine the alleged attack.


Privacy concerns form central part of petition

Vitraya has also framed the alleged breach as a constitutional privacy issue rather than solely a dispute between competing businesses.

The petition relies on the Supreme Court's 2017 judgment in Justice K.S. Puttaswamy (Retd.) v. Union of India, in which a nine-judge Constitution Bench recognised privacy as a fundamental right protected under Article 21. The court held that privacy is intrinsic to the protection of life and personal liberty.

That constitutional framework is relevant to a case involving medical information because the alleged data does not merely concern commercial records. It potentially connects individuals with information about their health, treatment and insurance claims.

The petition consequently argues that the alleged unauthorised disclosure of such information affects citizens' informational privacy and digital autonomy.


India's data protection framework adds another layer

The case also arrives as India moves toward implementing its newer personal-data protection regime.

The Digital Personal Data Protection Act, 2023 establishes a framework governing the processing of digital personal data and creates obligations for organisations handling such information. The Act also provides for a Data Protection Board of India and includes provisions addressing data-fiduciary obligations, individual rights, grievance redressal and penalties.

However, the timing matters. The DPDP framework is being implemented in phases. The government notified the DPDP Rules in November 2025, while several substantive provisions of the Act and Rules are scheduled to take effect 18 months after the notification.

The alleged Vitraya intrusion was identified in February 2025, before those later implementation stages. The investigation therefore cannot simply be described as a test of the fully operational DPDP regime. Instead, the case sits at the intersection of India's existing cybercrime laws, constitutional privacy protections and the country's transition toward a dedicated personal-data protection framework.

Separately, CERT-In's directions under the Information Technology Act identify unauthorised access to IT systems or data, data breaches and data leaks among cybersecurity incidents that covered organisations are required to report.


Supreme Court seeks response on proposed CBI investigation

The Supreme Court's immediate action is limited to issuing notice on the petition. The court has not made a finding that the alleged breach occurred in the manner claimed by Vitraya, nor has it established the involvement of the companies named in the petition.

The petitioner is asking the court to transfer the investigation to the CBI because it considers the existing police investigation inadequate.

Alternatively, Vitraya has proposed a court-monitored SIT involving agencies with relevant cybersecurity expertise, including the CBI and CERT-In.

The company's argument is that the combination of alleged cross-state activity, foreign-hosted infrastructure, sensitive medical information, multiple corporate entities and digital forensic evidence makes the case unsuitable for a routine investigation.

The Supreme Court's notice now places the investigation and the requested transfer before the respondents, including the Union government, the CBI and the Punjab government.

The case could therefore become an important test of how Indian authorities investigate alleged large-scale breaches involving healthcare data, cross-border infrastructure and competing corporate entities, particularly when the affected information includes medical records and government-linked identifiers.

For now, however, the allegations remain subject to investigation and judicial consideration.

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